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1.  Promoting synergistic research and education in genomics and bioinformatics 
BMC Genomics  2008;9(Suppl 1):I1.
Bioinformatics and Genomics are closely related disciplines that hold great promises for the advancement of research and development in complex biomedical systems, as well as public health, drug design, comparative genomics, personalized medicine and so on. Research and development in these two important areas are impacting the science and technology.
High throughput sequencing and molecular imaging technologies marked the beginning of a new era for modern translational medicine and personalized healthcare. The impact of having the human sequence and personalized digital images in hand has also created tremendous demands of developing powerful supercomputing, statistical learning and artificial intelligence approaches to handle the massive bioinformatics and personalized healthcare data, which will obviously have a profound effect on how biomedical research will be conducted toward the improvement of human health and prolonging of human life in the future. The International Society of Intelligent Biological Medicine (http://www.isibm.org) and its official journals, the International Journal of Functional Informatics and Personalized Medicine (http://www.inderscience.com/ijfipm) and the International Journal of Computational Biology and Drug Design (http://www.inderscience.com/ijcbdd) in collaboration with International Conference on Bioinformatics and Computational Biology (Biocomp), touch tomorrow's bioinformatics and personalized medicine throughout today's efforts in promoting the research, education and awareness of the upcoming integrated inter/multidisciplinary field. The 2007 international conference on Bioinformatics and Computational Biology (BIOCOMP07) was held in Las Vegas, the United States of American on June 25-28, 2007. The conference attracted over 400 papers, covering broad research areas in the genomics, biomedicine and bioinformatics. The Biocomp 2007 provides a common platform for the cross fertilization of ideas, and to help shape knowledge and scientific achievements by bridging these two very important disciplines into an interactive and attractive forum. Keeping this objective in mind, Biocomp 2007 aims to promote interdisciplinary and multidisciplinary education and research. 25 high quality peer-reviewed papers were selected from 400+ submissions for this supplementary issue of BMC Genomics. Those papers contributed to a wide-range of important research fields including gene expression data analysis and applications, high-throughput genome mapping, sequence analysis, gene regulation, protein structure prediction, disease prediction by machine learning techniques, systems biology, database and biological software development. We always encourage participants submitting proposals for genomics sessions, special interest research sessions, workshops and tutorials to Professor Hamid R. Arabnia (hra@cs.uga.edu) in order to ensure that Biocomp continuously plays the leadership role in promoting inter/multidisciplinary research and education in the fields. Biocomp received top conference ranking with a high score of 0.95/1.00. Biocomp is academically co-sponsored by the International Society of Intelligent Biological Medicine and the Research Laboratories and Centers of Harvard University – Massachusetts Institute of Technology, Indiana University - Purdue University, Georgia Tech – Emory University, UIUC, UCLA, Columbia University, University of Texas at Austin and University of Iowa etc. Biocomp - Worldcomp brings leading scientists together across the nation and all over the world and aims to promote synergistic components such as keynote lectures, special interest sessions, workshops and tutorials in response to the advances of cutting-edge research.
doi:10.1186/1471-2164-9-S1-I1
PMCID: PMC3226105  PMID: 18366597
2.  Advanced Paternal Age Is Associated with Impaired Neurocognitive Outcomes during Infancy and Childhood 
PLoS Medicine  2009;6(3):e1000040.
Background
Advanced paternal age (APA) is associated with an increased risk of neurodevelopmental disorders such as autism and schizophrenia, as well as with dyslexia and reduced intelligence. The aim of this study was to examine the relationship between paternal age and performance on neurocognitive measures during infancy and childhood.
Methods and Findings
A sample of singleton children (n = 33,437) was drawn from the US Collaborative Perinatal Project. The outcome measures were assessed at 8 mo, 4 y, and 7 y (Bayley scales, Stanford Binet Intelligence Scale, Graham-Ernhart Block Sort Test, Wechsler Intelligence Scale for Children, Wide Range Achievement Test). The main analyses examined the relationship between neurocognitive measures and paternal or maternal age when adjusted for potential confounding factors. Advanced paternal age showed significant associations with poorer scores on all of the neurocognitive measures apart from the Bayley Motor score. The findings were broadly consistent in direction and effect size at all three ages. In contrast, advanced maternal age was generally associated with better scores on these same measures.
Conclusions
The offspring of older fathers show subtle impairments on tests of neurocognitive ability during infancy and childhood. In light of secular trends related to delayed fatherhood, the clinical implications and the mechanisms underlying these findings warrant closer scrutiny.
Using a sample of children from the US Collaborative Perinatal Project, John McGrath and colleagues show that the offspring of older fathers exhibit subtle impairments on tests of neurocognitive ability during infancy and childhood.
Editors' Summary
Background.
Over the last few decades, changes in society in the developed world have made it increasingly common for couples to wait until their late thirties to have children. In 1993, 25% of live births within marriage in England and Wales were to fathers aged 35–54 years, but by 2003 it was 40%. It is well known that women's fertility declines with age and that older mothers are more likely to have children with disabilities such as Down's syndrome. In contrast, many men can father children throughout their lives, and little attention has been paid to the effects of older fatherhood.
More recent evidence shows that a man's age does affect both fertility and the child's health. “Advanced paternal age” has been linked to miscarriages, birth deformities, cancer, and specific behavioral problems such as autism or schizophrenia.
Rates of autism have increased in recent decades, but the cause is unknown. Studies of twins and families have suggested there may be a complex genetic basis, and it is suspected that damage to sperm, which can accumulate over a man's lifetime, may be responsible. A woman's eggs are formed largely while she is herself in the womb, but sperm-making cells divide throughout a man's lifetime, increasing the chance of mutations in sperm.
Why Was This Study Done?
There is good evidence linking specific disorders with older fathers, but the link between a father's age and a child's more general intelligence is not as clear. A recent study suggested a link between reduced intelligence and both very young and older fathers. The authors wanted to use this large dataset to test the idea that older fathers have children who do worse on tests of intelligence. They also wanted to re-examine others' findings using this same dataset that older mothers have more intelligent children.
What Did the Researchers Do and Find?
The researchers gathered no new data but reanalyzed data on children from the US Collaborative Perinatal Project (CPP), which had used a variety of tests given to children at ages 8 months, 4 years, and 7 years, to measure cognitive ability—the ability to think and reason, including concentration, memory, learning, understanding, speaking, and reading. Some tests included assessments of “motor skills”—physical co-ordination.
The CPP dataset holds information on children of 55,908 expectant mothers who attended 12 university-affiliated hospital clinics in the United States from 1959 to 1965. The researchers excluded premature babies and multiple births and chose one pregnancy at random for each eligible woman, to keep their analysis simpler. This approach reduced the number of children in their analysis to 33,437.
The researchers analyzed the data using two models. In one, they took into account physical factors such as the parents' ages. In the other, they also took into account social factors such as the parents' level of education and income, which are linked to intelligence. In addition, the authors grouped the children by their mother's age and, within each group, looked for a link between the lowest-scoring children and the age of their father.
The researchers found that children with older fathers had lower scores on all of the measures except one measure of motor skills. In contrast, children with older mothers had higher scores. They found that the older the father, the more likely was this result found.
What Do These Findings Mean?
This study is the first to show that children of older fathers perform less well in a range of tests when young, but cannot say whether those children catch up with their peers after the age of 7 years. Results may also be biased because information was more likely to be missing for children whose father's age was not recorded.
Previous researchers had proposed that children of older mothers may perform better in tests because they experience a more nurturing home environment. If this is the case, children of older fathers do not experience the same benefit.
However, further work needs to be done to confirm these findings. Especially in newer datasets, current trends to delay parenthood mean these findings have implications for individuals, couples, and policymakers. Individuals and couples need to be aware that the ages of both partners can affect their ability to have healthy children, though the risks for individual children are small. Policymakers should consider promoting awareness of the risks of delaying parenthood or introducing policies to encourage childbearing at an optimal age.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000040.
Mothers 35+ is a UK Web site with resources and information for older mothers, mothers-to-be, and would-be mothers, including information on the health implications of fathering a child late in life
The American Society for Reproductive Medicine published a Patient Information Booklet on Age and Fertility in 2003, which is available online; it contains a small section called “Fertility in the Aging Male,” but otherwise focuses on women
The online encyclopedia Wikipedia has a short article on the “Paternal age effect” (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
In 2005, the UK Office of National Statistics published a booklet entitled “Perpetual postponers? Women's, men's and couple's fertility intentions and subsequent fertility behaviour” looking at data from the British Household Panel Survey
doi:10.1371/journal.pmed.1000040
PMCID: PMC2653549  PMID: 19278291
3.  Case-based medical informatics 
Background
The "applied" nature distinguishes applied sciences from theoretical sciences. To emphasize this distinction, we begin with a general, meta-level overview of the scientific endeavor. We introduce the knowledge spectrum and four interconnected modalities of knowledge. In addition to the traditional differentiation between implicit and explicit knowledge we outline the concepts of general and individual knowledge. We connect general knowledge with the "frame problem," a fundamental issue of artificial intelligence, and individual knowledge with another important paradigm of artificial intelligence, case-based reasoning, a method of individual knowledge processing that aims at solving new problems based on the solutions to similar past problems.
We outline the fundamental differences between Medical Informatics and theoretical sciences and propose that Medical Informatics research should advance individual knowledge processing (case-based reasoning) and that natural language processing research is an important step towards this goal that may have ethical implications for patient-centered health medicine.
Discussion
We focus on fundamental aspects of decision-making, which connect human expertise with individual knowledge processing. We continue with a knowledge spectrum perspective on biomedical knowledge and conclude that case-based reasoning is the paradigm that can advance towards personalized healthcare and that can enable the education of patients and providers.
We center the discussion on formal methods of knowledge representation around the frame problem. We propose a context-dependent view on the notion of "meaning" and advocate the need for case-based reasoning research and natural language processing. In the context of memory based knowledge processing, pattern recognition, comparison and analogy-making, we conclude that while humans seem to naturally support the case-based reasoning paradigm (memory of past experiences of problem-solving and powerful case matching mechanisms), technical solutions are challenging.
Finally, we discuss the major challenges for a technical solution: case record comprehensiveness, organization of information on similarity principles, development of pattern recognition and solving ethical issues.
Summary
Medical Informatics is an applied science that should be committed to advancing patient-centered medicine through individual knowledge processing. Case-based reasoning is the technical solution that enables a continuous individual knowledge processing and could be applied providing that challenges and ethical issues arising are addressed appropriately.
doi:10.1186/1472-6947-4-19
PMCID: PMC544898  PMID: 15533257
4.  Virtual Neurorobotics (VNR) to Accelerate Development of Plausible Neuromorphic Brain Architectures 
Traditional research in artificial intelligence and machine learning has viewed the brain as a specially adapted information-processing system. More recently the field of social robotics has been advanced to capture the important dynamics of human cognition and interaction. An overarching societal goal of this research is to incorporate the resultant knowledge about intelligence into technology for prosthetic, assistive, security, and decision support applications. However, despite many decades of investment in learning and classification systems, this paradigm has yet to yield truly “intelligent” systems. For this reason, many investigators are now attempting to incorporate more realistic neuromorphic properties into machine learning systems, encouraged by over two decades of neuroscience research that has provided parameters that characterize the brain's interdependent genomic, proteomic, metabolomic, anatomic, and electrophysiological networks. Given the complexity of neural systems, developing tenable models to capture the essence of natural intelligence for real-time application requires that we discriminate features underlying information processing and intrinsic motivation from those reflecting biological constraints (such as maintaining structural integrity and transporting metabolic products). We propose herein a conceptual framework and an iterative method of virtual neurorobotics (VNR) intended to rapidly forward-engineer and test progressively more complex putative neuromorphic brain prototypes for their ability to support intrinsically intelligent, intentional interaction with humans. The VNR system is based on the viewpoint that a truly intelligent system must be driven by emotion rather than programmed tasking, incorporating intrinsic motivation and intentionality. We report pilot results of a closed-loop, real-time interactive VNR system with a spiking neural brain, and provide a video demonstration as online supplemental material.
doi:10.3389/neuro.12.001.2007
PMCID: PMC2533586  PMID: 18958272
neurorobotic architecture; human robot interface; virtual reality; artificial intelligence; social robotics; epigenetic robotics; reinforcement learning; neocortex; mesocircuit
5.  A Survey on Ambient Intelligence in Health Care 
Ambient Intelligence (AmI) is a new paradigm in information technology aimed at empowering people’s capabilities by the means of digital environments that are sensitive, adaptive, and responsive to human needs, habits, gestures, and emotions. This futuristic vision of daily environment will enable innovative human-machine interactions characterized by pervasive, unobtrusive and anticipatory communications. Such innovative interaction paradigms make ambient intelligence technology a suitable candidate for developing various real life solutions, including in the health care domain. This survey will discuss the emergence of ambient intelligence (AmI) techniques in the health care domain, in order to provide the research community with the necessary background. We will examine the infrastructure and technology required for achieving the vision of ambient intelligence, such as smart environments and wearable medical devices. We will summarize of the state of the art artificial intelligence methodologies used for developing AmI system in the health care domain, including various learning techniques (for learning from user interaction), reasoning techniques (for reasoning about users’ goals and intensions) and planning techniques (for planning activities and interactions). We will also discuss how AmI technology might support people affected by various physical or mental disabilities or chronic disease. Finally, we will point to some of the successful case studies in the area and we will look at the current and future challenges to draw upon the possible future research paths.
doi:10.1109/JPROC.2013.2262913
PMCID: PMC3890262  PMID: 24431472
Ambient Intelligence; Health Care; Smart Environments; Sensor Networks
6.  Medical Expert Systems—Knowledge Tools for Physicians 
Western Journal of Medicine  1986;145(6):830-839.
Recent advances in the field of artificial intelligence have led to the emergence of expert systems, computational tools designed to capture and make available the knowledge of experts in a field. Although much of the underlying technology available today is derived from basic research on biomedical advice systems during the 1970s, medical application packages are thus far generally unavailable from the young artificial intelligence industry. Medical expert systems will begin to appear, however, as researchers in medical artificial intelligence continue to make progress in key areas such as knowledge acquisition, model-based reasoning and system integration for clinical environments. It is accordingly important for physicians to understand the current state of such research and the theoretic and logistic barriers that remain before useful systems can be made available. One experimental system, ONCOCIN, provides a glimpse of the kinds of knowledge-based tools that will someday be available to physicians.
Images
PMCID: PMC1307157  PMID: 3811349
7.  eHealth Research from the User’s Perspective 
American journal of preventive medicine  2007;32(5 Suppl):S97-103.
The application of Information Technology (IT) to issues of healthcare delivery has had a long and tortuous history in the U.S. Within the field of eHealth, vanguard applications of advanced computing techniques, such as applications in artificial intelligence or expert systems, have languished in spite of a track record of scholarly publication and decisional accuracy. The problem is one of purpose, of asking the right questions for the science to solve. Historically, many computer science pioneers have been tempted to ask “what can the computer do?” New advances in eHealth are prompting developers to ask “what can people do?” How can eHealth take part in national goals for healthcare reform to empower relationships between healthcare professionals and patients, healthcare teams and families, and hospitals and communities to improve health equitably throughout the population? To do this, eHealth researchers must combine best evidence from the user sciences (human factors engineering, human-computer interaction, psychology, and usability) with best evidence in medicine to create transformational improvements in the quality of care that medicine offers. These improvements should follow recommendations from the Institute of Medicine to create a health care system that is (a) safe, (b) effective (evidence-based), (c) patient-centered, and (d) timely. Relying on the eHealth researcher’s intuitive grasp of systems issues, improvements should be made with considerations of users and beneficiaries at the individual (patient/physician), group (family/staff), community, and broad environmental levels.
doi:10.1016/j.amepre.2007.01.019
PMCID: PMC1939873  PMID: 17466825
8.  New application of intelligent agents in sporadic amyotrophic lateral sclerosis identifies unexpected specific genetic background 
BMC Bioinformatics  2008;9:254.
Background
Few genetic factors predisposing to the sporadic form of amyotrophic lateral sclerosis (ALS) have been identified, but the pathology itself seems to be a true multifactorial disease in which complex interactions between environmental and genetic susceptibility factors take place. The purpose of this study was to approach genetic data with an innovative statistical method such as artificial neural networks to identify a possible genetic background predisposing to the disease. A DNA multiarray panel was applied to genotype more than 60 polymorphisms within 35 genes selected from pathways of lipid and homocysteine metabolism, regulation of blood pressure, coagulation, inflammation, cellular adhesion and matrix integrity, in 54 sporadic ALS patients and 208 controls. Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis
Results
Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis. An unexpected discovery of a strong genetic background in sporadic ALS using a DNA multiarray panel and analytical processing of the data with advanced artificial neural networks was found. The predictive accuracy obtained with Linear Discriminant Analysis and Standard Artificial Neural Networks ranged from 70% to 79% (average 75.31%) and from 69.1 to 86.2% (average 76.6%) respectively. The corresponding value obtained with Advanced Intelligent Systems reached an average of 96.0% (range 94.4 to 97.6%). This latter approach allowed the identification of seven genetic variants essential to differentiate cases from controls: apolipoprotein E arg158cys; hepatic lipase -480 C/T; endothelial nitric oxide synthase 690 C/T and glu298asp; vitamin K-dependent coagulation factor seven arg353glu, glycoprotein Ia/IIa 873 G/A and E-selectin ser128arg.
Conclusion
This study provides an alternative and reliable method to approach complex diseases. Indeed, the application of a novel artificial intelligence-based method offers a new insight into genetic markers of sporadic ALS pointing out the existence of a strong genetic background.
doi:10.1186/1471-2105-9-254
PMCID: PMC2443147  PMID: 18513389
9.  Introduction of a New Diagnostic Method for Breast Cancer Based on Fine Needle Aspiration (FNA) Test Data and Combining Intelligent Systems 
Background
Accurate Diagnosis of Breast Cancer is of prime importance. Fine Needle Aspiration test or "FNA”, which has been used for several years in Europe, is a simple, inexpensive, noninvasive and accurate technique for detecting breast cancer. Expending the suitable features of the Fine Needle Aspiration results is the most important diagnostic problem in early stages of breast cancer. In this study, we introduced a new algorithm that can detect breast cancer based on combining artificial intelligent system and Fine Needle Aspiration (FNA).
Methods
We studied the Features of Wisconsin Data Base Cancer which contained about 569 FNA test samples (212 patient samples (malignant) and 357 healthy samples (benign)). In this research, we combined Artificial Intelligence Approaches, such as Evolutionary Algorithm (EA) with Genetic Algorithm (GA), and also used Exact Classifier Systems (here by Fuzzy C-Means (FCM)) to separate malignant from benign samples. Furthermore, we examined artificial Neural Networks (NN) to identify the model and structure. This research proposed a new algorithm for an accurate diagnosis of breast cancer.
Results
According to Wisconsin Data Base Cancer (WDBC) data base, 62.75% of samples were benign, and 37.25% were malignant. After applying the proposed algorithm, we achieved high detection accuracy of about "96.579%” on 205 patients who were diagnosed as having breast cancer. It was found that the method had 93% sensitivity, 73% specialty, 65% positive predictive value, and 95% negative predictive value, respectively. If done by experts, Fine Needle Aspiration (FNA) can be a reliable replacement for open biopsy in palpable breast masses. Evaluation of FNA samples during aspiration can decrease insufficient samples. FNA can be the first line of diagnosis in women with breast masses, at least in deprived regions, and may increase health standards and clinical supervision of patients.
Conclusion
Such a smart, economical, non-invasive, rapid and accurate system can be introduced as a useful diagnostic system for comprehensive treatment of breast cancer. Another advantage of this method is the possibility of diagnosing breast abnormalities. If done by experts, FNA can be a reliable replacement for open biopsy in palpable breast masses. Evaluation of FNA samples during aspiration can decrease insufficient samples.
PMCID: PMC4209568  PMID: 25352966
Breast cancer; Fine needle aspiration; Artificial intelligent
10.  Improving self-care of patients with chronic disease using online personal health record 
The Australasian Medical Journal  2012;5(9):517-521.
Background
Effective management of chronic diseases such as prostate cancer is important. Research suggests a tendency to use self-care treatment options such as over-the-counter (OTC) complementary medications among prostate cancer patients. The current trend in patient-driven recording of health data in an online Personal Health Record (PHR) presents an opportunity to develop new data-driven approaches for improving prostate cancer patient care. However, the ability of current online solutions to share patients’ data for better decision support is limited. An informatics approach may improve online sharing of self-care interventions among these patients. It can also provide better evidence to support decisions made during their self-managed care.
Aims
To identify requirements for an online system and describe a new case-based reasoning (CBR) method for improving self-care of advanced prostate cancer patients in an online PHR environment.
Method
A non-identifying online survey was conducted to understand self-care patterns among prostate cancer patients and to identify requirements for an online information system. The pilot study was carried out between August 2010 and December 2010. A case-base of 52 patients was developed.
Results
The data analysis showed self-care patterns among the prostate cancer patients. Selenium (55%) was the common complementary supplement used by the patients. Paracetamol (about 45%) was the commonly used OTC by the patients.
Conclusion
The results of this study specified requirements for an online case-based reasoning information system. The outcomes of this study are being incorporated in design of the proposed Artificial Intelligence (Al) driven patient journey browser system. A basic version of the proposed system is currently being considered for implementation.
doi:10.4066/AMJ.2012.1358
PMCID: PMC3477782  PMID: 23115588
Advanced Prostate Cancer; Self-care; Patient Journey; PHR; Case-based reasoning
11.  Intelligent Chiral Sensing Based on Supramolecular and Interfacial Concepts 
Sensors (Basel, Switzerland)  2010;10(7):6796-6820.
Of the known intelligently-operating systems, the majority can undoubtedly be classed as being of biological origin. One of the notable differences between biological and artificial systems is the important fact that biological materials consist mostly of chiral molecules. While most biochemical processes routinely discriminate chiral molecules, differentiation between chiral molecules in artificial systems is currently one of the challenging subjects in the field of molecular recognition. Therefore, one of the important challenges for intelligent man-made sensors is to prepare a sensing system that can discriminate chiral molecules. Because intermolecular interactions and detection at surfaces are respectively parts of supramolecular chemistry and interfacial science, chiral sensing based on supramolecular and interfacial concepts is a significant topic. In this review, we briefly summarize recent advances in these fields, including supramolecular hosts for color detection on chiral sensing, indicator-displacement assays, kinetic resolution in supramolecular reactions with analyses by mass spectrometry, use of chiral shape-defined polymers, such as dynamic helical polymers, molecular imprinting, thin films on surfaces of devices such as QCM, functional electrodes, FET, and SPR, the combined technique of magnetic resonance imaging and immunoassay, and chiral detection using scanning tunneling microscopy and cantilever technology. In addition, we will discuss novel concepts in recent research including the use of achiral reagents for chiral sensing with NMR, and mechanical control of chiral sensing. The importance of integration of chiral sensing systems with rapidly developing nanotechnology and nanomaterials is also emphasized.
doi:10.3390/s100706796
PMCID: PMC3231122  PMID: 22163577
chiral sensing; supramolecular chemistry; interface; molecular recognition; nanotechnology; nanomaterial
12.  Cooperation and the evolution of intelligence 
The high levels of intelligence seen in humans, other primates, certain cetaceans and birds remain a major puzzle for evolutionary biologists, anthropologists and psychologists. It has long been held that social interactions provide the selection pressures necessary for the evolution of advanced cognitive abilities (the ‘social intelligence hypothesis’), and in recent years decision-making in the context of cooperative social interactions has been conjectured to be of particular importance. Here we use an artificial neural network model to show that selection for efficient decision-making in cooperative dilemmas can give rise to selection pressures for greater cognitive abilities, and that intelligent strategies can themselves select for greater intelligence, leading to a Machiavellian arms race. Our results provide mechanistic support for the social intelligence hypothesis, highlight the potential importance of cooperative behaviour in the evolution of intelligence and may help us to explain the distribution of cooperation with intelligence across taxa.
doi:10.1098/rspb.2012.0206
PMCID: PMC3385471  PMID: 22496188
reciprocity; Machiavellian intelligence; cognition; social brain; prisoner's dilemma; snowdrift game
13.  The intelligence paradox; will ET get the metabolic syndrome? Lessons from and for Earth 
Mankind is facing an unprecedented health challenge in the current pandemic of obesity and diabetes. We propose that this is the inevitable (and predictable) consequence of the evolution of intelligence, which itself could be an expression of life being an information system driven by entropy. Because of its ability to make life more adaptable and robust, intelligence evolved as an efficient adaptive response to the stresses arising from an ever-changing environment. These adaptive responses are encapsulated by the epiphenomena of “hormesis”, a phenomenon we believe to be central to the evolution of intelligence and essential for the maintenance of optimal physiological function and health. Thus, as intelligence evolved, it would eventually reach a cognitive level with the ability to control its environment through technology and have the ability remove all stressors. In effect, it would act to remove the very hormetic factors that had driven its evolution. Mankind may have reached this point, creating an environmental utopia that has reduced the very stimuli necessary for optimal health and the evolution of intelligence – “the intelligence paradox”. One of the hallmarks of this paradox is of course the rising incidence in obesity, diabetes and the metabolic syndrome. This leads to the conclusion that wherever life evolves, here on earth or in another part of the galaxy, the “intelligence paradox” would be the inevitable side-effect of the evolution of intelligence. ET may not need to just “phone home” but may also need to “phone the local gym”. This suggests another possible reason to explain Fermi’s paradox; Enrico Fermi, the famous physicist, suggested in the 1950s that if extra-terrestrial intelligence was so prevalent, which was a common belief at the time, then where was it? Our suggestion is that if advanced life has got going elsewhere in our galaxy, it can’t afford to explore the galaxy because it has to pay its healthcare costs.
doi:10.1186/1743-7075-11-34
PMCID: PMC4118160  PMID: 25089149
Intelligence; Obesity; Hormesis; Exercise; Metabolic syndrome; Type 2 diabetes; Environment; Aging; Mitochondria; Proton gradients; Evolution; Fermi paradox; Entropy
14.  The Nigerian health care system: Need for integrating adequate medical intelligence and surveillance systems 
Objectives:
As an important element of national security, public health not only functions to provide adequate and timely medical care but also track, monitor, and control disease outbreak. The Nigerian health care had suffered several infectious disease outbreaks year after year. Hence, there is need to tackle the problem. This study aims to review the state of the Nigerian health care system and to provide possible recommendations to the worsening state of health care in the country. To give up-to-date recommendations for the Nigerian health care system, this study also aims at reviewing the dynamics of health care in the United States, Britain, and Europe with regards to methods of medical intelligence/surveillance.
Materials and Methods:
Databases were searched for relevant literatures using the following keywords: Nigerian health care, Nigerian health care system, and Nigerian primary health care system. Additional keywords used in the search were as follows: United States (OR Europe) health care dynamics, Medical Intelligence, Medical Intelligence systems, Public health surveillance systems, Nigerian medical intelligence, Nigerian surveillance systems, and Nigerian health information system. Literatures were searched in scientific databases Pubmed and African Journals OnLine. Internet searches were based on Google and Search Nigeria.
Results:
Medical intelligence and surveillance represent a very useful component in the health care system and control diseases outbreak, bioattack, etc. There is increasing role of automated-based medical intelligence and surveillance systems, in addition to the traditional manual pattern of document retrieval in advanced medical setting such as those in western and European countries.
Conclusion:
The Nigerian health care system is poorly developed. No adequate and functional surveillance systems are developed. To achieve success in health care in this modern era, a system well grounded in routine surveillance and medical intelligence as the backbone of the health sector is necessary, besides adequate management couple with strong leadership principles.
doi:10.4103/0975-7406.90100
PMCID: PMC3249694  PMID: 22219580
Health care; medical intelligence; medical surveillance systems; Nigeria; Nigerian health care system; public health
15.  Cultural Intelligence and Social Adaptability: A Comparison between Iranian and Non-Iranian Dormitory Students of Isfahan University of Medical Sciences 
Materia Socio-Medica  2013;25(1):40-43.
Introduction:
At the modern age, to acquire knowledge and experience, the individuals with their own specific culture have to enter contexts with cultural diversity, adapt to different cultures and have social interactions to be able to have effective inter-cultural relationships.To have such intercultural associations and satisfy individual needs in the society, cultural intelligence and social adaptability are deemed as inevitable requirements, in particular for those who enter a quite different culture. Hence, the present study tries to compare the cultural intelligence and its aspects and social adaptability in Iranian and non-Iranian dormitory students of Isfahan University of Medical Sciences in 2012.
Methodology:
The study was of descriptiveanalytical nature. The research population consisted of Iranian and non-Iranian students resided in the dormitories of Isfahan University of Medical Sciences which are 2500, totally. For Iranian students, two-stage sampling method was adopted. At the first stage, classified sampling and at the second stage, systematic random sampling was conducted. In this way, 441 students were selected. To form non-Iranian students’ sample, consensus sampling method was applied and a sample of 37 students were obtained. The research data was collected by using Earley & Ang’s Cultural Intelligence Questionnaire with the Cronbach’s coefficient α of 76% and California Social Adaptability Standard Questionnaire with the Cronbach’s coefficient α of over 70%. Then, the data were put into SPSS software to be analyzed. Finally, the results were presented by descriptive and inferential statistics methods.
Results:
The study findings revealed that there was no statistically significant difference between cultural intelligence and cognitive aspect of cultural intelligence in Iranian and non-Iranian students (P≥0/05). However, Iranian and non-Iranian students statistically differed in terms of the following aspects of cultural intelligence: meta-cognitive aspect (61.8% for Iranian students vs. 47.6% for non-Iranians), motivational aspect (59.0% vs. 42.6%), behavioral aspect (31.8% vs. 41.2%) as well as social adaptability as the other variable in question ( 68.9% vs. 56.2%) (p<0.001).
Conclusion:
The comparison of the mean scores gained for meta-cognitive and motivational aspects of cultural intelligence as well as social adaptability in Iranian and non-Iranian students resided in the dormitories of Isfahan University of Medical Sciences revealed that the Iranian students had the higher rank. On the other hand, the mean score acquired for the behavioral aspect in Iranian and non-Iranian students were comparable, with non-Iranian students having the higher mean scores. Therefore, it can be said that the meta-cognitive and motivational aspects of cultural intelligence and social adaptability of non-Iranian students and the behavioral aspect of Iranian students’ cultural intelligence may be promoted by educational planning, thereby, taking effective steps towards their achievement in contexts with inter-cultural interaction . In this way, their mental health will be enhanced, as well.
doi:10.5455/msm.2013.25.40-43
PMCID: PMC3633545  PMID: 23678339
culture; intelligence; cultural intelligence; social adaptability.
16.  The relationship between cultural intelligence and social compatibility in Isfahan University of Medical Sciences dormitories resident students 
Introduction:
Cultural intelligence and social compatibility are two acquired processes that their education and reinforcement between dormitory's students who have inter cultural interactions with each other can conclude with results that tension diminution, inter cultural contrast and conflict, social divisions and consequently healthy and peaceful relationships and governance and finally mental peace, and health are of its most important. Hence, the research has been occurring in order to the determination of cultural intelligence relationship with the social compatibility of Isfahan University of Medical Sciences dormitories resident students in 2012.
Materials and Methods:
The research method is descriptive-correlation, and its population is composed of all Isfahan University of Medical Sciences dormitories resident students in 2012 that were totally 2500 persons. The two steps sampling method have been used, group sampling and random sampling has been occurring at first and second steps and totally 447 persons were selected. Research data were collected via Earley and Ang cultural intelligence questionnaire with 0.76 Cronbach's alpha Coefficient and California social compatibility standard questionnaire with higher than 0.70 Cronbach's alpha factor. Questionnaire data have been analyzed with the SPSS software and results have been presented in the shape of descriptions and statistics.
Findings:
Results showed that there is a direct significant relationship (P < 0.001) between cultural intelligence and the social adjustment in students living in Isfahan University of Medical Sciences dormitories and also there is a direct significant relationship in the level of (P < 0.05) between cognitive and motivational dimensions of cultural intelligence; however, there is no significant relationship between cognitive and behavioral dimensions of cultural intelligence and social adjustment (P > 0.05).
Conclusion:
Cultural intelligence and cognitive and motivational addition in dimensions of students living in Isfahan University of Medical Sciences dormitories increase their social integration, therefore, cultural intelligence and social adjustment of students can be increased through planning and we can try for their mental health by this way.
doi:10.4103/2277-9531.139682
PMCID: PMC4165095  PMID: 25250366
Cultural intelligence; social adjustment; Students
17.  Judgment of the Humanness of an Interlocutor Is in the Eye of the Beholder 
PLoS ONE  2011;6(9):e25085.
Despite tremendous advances in artificial language synthesis, no machine has so far succeeded in deceiving a human. Most research focused on analyzing the behavior of “good” machine. We here choose an opposite strategy, by analyzing the behavior of “bad” humans, i.e., humans perceived as machine. The Loebner Prize in Artificial Intelligence features humans and artificial agents trying to convince judges on their humanness via computer-mediated communication. Using this setting as a model, we investigated here whether the linguistic behavior of human subjects perceived as non-human would enable us to identify some of the core parameters involved in the judgment of an agents' humanness. We analyzed descriptive and semantic aspects of dialogues in which subjects succeeded or failed to convince judges of their humanness. Using cognitive and emotional dimensions in a global behavioral characterization, we demonstrate important differences in the patterns of behavioral expressiveness of the judges whether they perceived their interlocutor as being human or machine. Furthermore, the indicators of interest displayed by the judges were predictive of the final judgment of humanness. Thus, we show that the judgment of an interlocutor's humanness during a social interaction depends not only on his behavior, but also on the judge himself. Our results thus demonstrate that the judgment of humanness is in the eye of the beholder.
doi:10.1371/journal.pone.0025085
PMCID: PMC3178592  PMID: 21966420
18.  Controlling anxiety in physicians and nurses working in intensive care units using emotional intelligence items as an anxiety management tool in Iran 
Introduction:
Today, anxiety is one of the most common problems of mankind, to the extent that we could claim that it predisposes human to many physical illnesses, mental disorders, behavioral disturbances, and inappropriate reactions. The intensive care unit is a stressful environment for its staff, especially physicians and nurses. These stresses may have negative effects on the mental health and performance of the nurses and physicians. But the complications caused by this stress can be prevented by training emotional intelligence components. In this study, the impact of training emotional intelligence components on stress and anxiety in nurses and expert physicians is examined.
Methodology:
A cross-interventional, pre- to post-, case and control group design was used and inferential study design was implemented. Our study included 150 registered hospitals physicians and nurses, who were widely distributed. In the study, a ten-question demographic questionnaire, a 20-question situational anxiety Berger (overt) questionnaire, and a 133-question Bar-on emotional intelligence questionnaire were used.
Results:
Research results indicate that average score for the situational anxiety of the case group in nurses was 47.20 before the intervention and it was reduced to 42.00 after the intervention, and in physicians was 40.46 before the intervention and it decreased to 33.66 after implementation of training items of emotional intelligence, which indicates the impact of training of emotional intelligence components on reduction of situational anxiety. The average score of situational anxiety of control group nurses was 46.73 before the intervention and it decreased to 45.70. In physicians, it was 38.33 before the intervention and it increased to 39.40 during post-test. However, t-test did not confirmed a statistically significant difference between the average score of situational anxiety of both case and control groups before the intervention, and there was a statistically significant difference between the average score of both case and control groups after training components of emotional intelligence (P = 0.000).
Conclusion:
Training emotional intelligence components reduces situational anxiety of nurses and physicians working in intensive care units and their emotional intelligence score increased and situational anxiety score was significantly reduced.
doi:10.2147/IJGM.S25850
PMCID: PMC3259021  PMID: 22259255
emotional intelligence; training; anxiety; nurses and physicians; intensive care units
19.  Emotional intelligence, emotional labor, and job satisfaction among physicians in Greece 
Background
There is increasing evidence that psychological constructs, such as emotional intelligence and emotional labor, play an important role in various organizational outcomes in service sector. Recently, in the “emotionally charged” healthcare field, emotional intelligence and emotional labor have both emerged as research tools, rather than just as theoretical concepts, influencing various organizational parameters including job satisfaction. The present study aimed at investigating the relationships, direct and/or indirect, between emotional intelligence, the surface acting component of emotional labor, and job satisfaction in medical staff working in tertiary healthcare.
Methods
Data were collected from 130 physicians in Greece, who completed a series of self-report questionnaires including: a) the Wong Law Emotional Intelligence Scale, which assessed the four dimensions of emotional intelligence, i.e. Self-Emotion Appraisal, Others’ Emotion Appraisal, Use of Emotion, and Regulation of Emotion, b) the General Index of Job Satisfaction, and c) the Dutch Questionnaire on Emotional Labor (surface acting component).
Results
Emotional intelligence (Use of Emotion dimension) was significantly and positively correlated with job satisfaction (r=.42, p<.001), whereas a significant negative correlation between surface acting and job satisfaction was observed (r=−.39, p<.001). Furthermore, Self-Emotion Appraisal was negatively correlated with surface acting (r=−.20, p<.01). Self-Emotion Appraisal was found to influence job satisfaction both directly and indirectly through surface acting, while this indirect effect was moderated by gender. Apart from its mediating role, surface acting was also a moderator of the emotional intelligence-job satisfaction relationship. Hierarchical multiple regression analysis revealed that surface acting could predict job satisfaction over and above emotional intelligence dimensions.
Conclusions
The results of the present study may contribute to the better understanding of emotion-related parameters that affect the work process with a view to increasing the quality of service in the health sector.
doi:10.1186/1472-6963-12-463
PMCID: PMC3541956  PMID: 23244390
Emotional intelligence; Emotional labor; Surface acting; Job satisfaction; Greece
20.  The relationship between emotional intelligence health and marital satisfaction: A comparative study 
Introduction:
Marriage is known as the most important incident in everyone's life after birth. The most important purpose of marriage is achieving a life followed with love and affection beside the spouse and providing mental comfort and general health. The aim of the present study is to investigate the relationship between emotional intelligence health and marital satisfaction among married people.
Materials and Methods:
The research method is descriptive- analytic and its design is comparative, done on 226 people including 114 persons (50 women and 64 men) having marital conflicts, and 112 people (58 women and 54 men) having marital satisfaction, by cluster random sampling from 13 districts of the city of Isfahan. Bar-on (with 90 questions) and Enrich marital satisfaction (115 questions) questionnaires were used for collecting the required information. The data was analyzed using descriptive statistics including independent t-tests, Pearson correlation, and linear regression analysis, using SPSS software version 19.
Results:
The results from the research showed that the scores of emotional intelligence in married people group having marriage conflicts who had referred to the administration of justice was 57.3 ± 13.2, and the random sample from the married people in the city of Isfahan as the comparing group had the score of 67.2 ± 9.5, and the difference of the average scores for the emotional intelligence for the two groups was significant (P < 0.001). The correlation analysis showed that there was a significant and positive relation between emotional intelligence and marital satisfaction (P < 0.001, r = 0.529). The results of linear regression also showed that the general emotional intelligence predicts the quality of marital satisfaction. The emotion of the predicting line of the marital satisfaction score (y) is in the form of: y = 14.8 + 0.656x, by using the emotional intelligence score (x).
Conclusion:
Regarding the close relations between emotional intelligence and marital satisfaction, education centers such as universities, organizations and family clinics could use this variable in micro- and macro-social plans for improving the quality of the married people relations and promoting health of the families and the society.
doi:10.4103/2277-9531.127616
PMCID: PMC3977397  PMID: 24741664
Emotional intelligence; general health; marital satisfaction; married people
21.  HIV Drug-Resistant Patient Information Management, Analysis, and Interpretation 
JMIR Research Protocols  2012;1(1):e3.
Introduction
The science of information systems, management, and interpretation plays an important part in the continuity of care of patients. This is becoming more evident in the treatment of human immunodeficiency virus (HIV) and acquired immune deficiency syndrome (AIDS), the leading cause of death in sub-Saharan Africa. The high replication rates, selective pressure, and initial infection by resistant strains of HIV infer that drug resistance will inevitably become an important health care concern. This paper describes proposed research with the aim of developing a physician-administered, artificial intelligence-based decision support system tool to facilitate the management of patients on antiretroviral therapy.
Methods
This tool will consist of (1) an artificial intelligence computer program that will determine HIV drug resistance information from genomic analysis; (2) a machine-learning algorithm that can predict future CD4 count information given a genomic sequence; and (3) the integration of these tools into an electronic medical record for storage and management.
Conclusion
The aim of the project is to create an electronic tool that assists clinicians in managing and interpreting patient information in order to determine the optimal therapy for drug-resistant HIV patients.
doi:10.2196/resprot.1930
PMCID: PMC3626142  PMID: 23611761
Medical Informatics; Bioinformatics; HIV drug resistance; Machine Learning
22.  Knowledge-based provision of home care e-services for the elderly and disabled 
Introduction
Elderly chronic patients are an increasing population using more and more national health services all around Europe. One way to better manage this social and economic challenge is to improve home care through the introduction of information and communication technologies (ICTs).
Description
The K4Care European research project has developed a web-based multi-agent platform providing the medical and management e-services required in a home care system. Due to the comorbidity of the typical patients of this application, the tool allows medical practitioners to define fully personalised care treatments (Individual Intervention Plans). Each of them involves the execution of diverse actions from different actors of the system. Every actor deals with an intelligent agent of the K4Care platform. Agents coordinate their activities autonomously in order to efficiently execute these personalised plans under the supervision of practitioners. Moreover, all the behaviour of the system is guided dynamically by the organisational and medical knowledge represented in the form of ontologies and formal intervention plans.
Conclusion
The prototype developed in the K4Care project can be taken as a proof-of-concept of the viability of improving home care assistance in the near future by using a combination of artificial intelligence methodologies, medical knowledge and ICTs.
PMCID: PMC2707557
home care e-services; elderly; disabled; ontologies; medical knowledge; information and communication technologies
23.  A novel AIDS/HIV intelligent medical consulting system based on expert systems 
Background:
The purpose of this paper is to propose a novel intelligent model for AIDS/HIV data based on expert system and using it for developing an intelligent medical consulting system for AIDS/HIV.
Materials and Methods:
In this descriptive research, 752 frequently asked questions (FAQs) about AIDS/HIV are gathered from numerous websites about this disease. To perform the data mining and extracting the intelligent model, the 6 stages of Crisp method has been completed for FAQs. The 6 stages include: Business understanding, data understanding, data preparation, modelling, evaluation and deployment. C5.0 Tree classification algorithm is used for modelling. Also, rational unified process (RUP) is used to develop the web-based medical consulting software. Stages of RUP are as follows: Inception, elaboration, construction and transition. The intelligent developed model has been used in the infrastructure of the software and based on client's inquiry and keywords related FAQs are displayed to the client, according to the rank. FAQs’ ranks are gradually determined considering clients reading it. Based on displayed FAQs, test and entertainment links are also displayed.
Result:
The accuracy of the AIDS/HIV intelligent web-based medical consulting system is estimated to be 78.76%.
Conclusion:
AIDS/HIV medical consulting systems have been developed using intelligent infrastructure. Being equipped with an intelligent model, providing consulting services on systematic textual data and providing side services based on client's activities causes the implemented system to be unique. The research has been approved by Iranian Ministry of Health and Medical Education for being practical.
doi:10.4103/2277-9531.119041
PMCID: PMC3826025  PMID: 24251290
AIDS/HIV; data mining; intelligent system; medical informatics; software engineering; text mining
24.  Spiritual Intelligence, Resiliency, and Withdrawal Time in Clients of Methadone Maintenance Treatment 
Background:
Reports show an increasing interest in spirituality. It has been revealed that people with spiritual tendencies, can better deal with a trauma, manage the stressful situations, and have greater improvement in their health condition.
Objectives:
Our aim was to examine the relationship between spiritual intelligence and resiliency, and the relation of these two variables with the withdrawal time of individuals treated with methadone.
Materials and Methods:
This research was conducted on patients referred to the addiction center of Baharan Psychiatric Hospital in Zahedan, Iran. Our sample included 100 referrals; they were provided with questionnaires and asked to answer them honestly. King’s spiritual intelligence questionnaire and resilience questionnaires were used.
Results:
There were significant positive correlations between resiliency and scores of spiritual intelligence as well as with subscales of spiritual intelligence. In addition, there were significant positive correlations between withdrawal time and scores of spiritual intelligence as well as with subscales of spiritual intelligence as well as with resiliency.
Conclusions:
Relationships between the spiritual intelligence and resiliency parameters with withdrawal time show that these parameters can have a role in relapse protection among addicted people.
doi:10.5812/ijhrba.11308
PMCID: PMC4070160  PMID: 24971291
Intelligence; Substance-Related Disorders; Recurrence
25.  The Coming of Age of Artificial Intelligence in Medicine* 
Summary
This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in medicine as being in its “adolescence” (Shortliffe EH. The adolescence of AI in medicine: Will the field come of age in the ‘90s? Artificial Intelligence in Medicine 1993; 5:93–106). In this article, the discussants reflect on medical AI research during the subsequent years and attempt to characterize the maturity and influence that has been achieved to date. Participants focus on their personal areas of expertise, ranging from clinical decision making, reasoning under uncertainty, and knowledge representation to systems integration, translational bioinformatics, and cognitive issues in both the modeling of expertise and the creation of acceptable systems.
doi:10.1016/j.artmed.2008.07.017
PMCID: PMC2752210  PMID: 18790621

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