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1.  A Virtual Notebook for biomedical work groups. 
During the past several years, Baylor College of Medicine has made a substantial commitment to the use of information technology in support of its corporate and academic programs. The concept of an Integrated Academic Information Management System (IAIMS) has proved central in our planning, and the IAIMS activities that we have undertaken with funding from the National Library of Medicine have proved to be important extensions of our technology development. Here we describe our Virtual Notebook system, a conceptual and technologic framework for task coordination and information management in biomedical work groups. When fully developed and deployed, the Virtual Notebook will improve the functioning of basic and clinical research groups in the college, and it currently serves as a model for the longer-term development of our entire information management environment.
PMCID: PMC227118  PMID: 3046694
2.  IAIMS development at Baylor College of Medicine. 
At Baylor College of Medicine, we are developing the technical and intellectual resources needed to realize the Integrated Academic Information Management System (IAIMS) concept fully. The substantial technical, organizational, and financial commitments involved demand that we align our efforts with the strategic purposes of the college. The support of science, therefore, has become the principal, but not exclusive, focus of Baylor's IAIMS effort. Even so, the information technology architecture we have created for biomedical research is proving valuable in other settings as well. And the infrastructure we are creating--the communications architecture and the linkages to information resources--serves many purposes in addition to those of research. The architecture accommodates a diversity of workstations, networks, and informational and computational servers. This will be the greatest possible chance of transferring the fruits of our Phase III development to other academic medical centers.
PMCID: PMC225664  PMID: 1326367
3.  Using Hypertext to Facilitate Information Sharing in Biomedical Research Groups 
As part of our effort to create an Integrated Academic Information Management System at Baylor College of Medicine, we are developing information technology to support the efforts of scientific work groups. Many of our ideas in this regard are embodied in a system called the Virtual Notebook which is intended to facilitate information sharing and management in such groups. Here we discuss the foundations of that system - a hypertext system that we have developed using a relational data base and the distributable interface the we have written in the X Window System.
PMCID: PMC2245694
4.  The development of a client application for the collaborative social and medical services system. 
This paper describes the design and implementation of a client application for the Baylor College of Medicine Teen Health Clinics. The application is the front end to the Collaborative Social and Medical Services System (CSMSS) under development by Baylor's Medical Informatics and Computing Research Program [8]. The application provides distributed access to an underlying object oriented database system. A process driven and patient centered design will provide staff members with a complete set of services, including forms for data entry and viewing, query, and access management to facilitate efficient and effective delivery of services. Role-specific interfaces will be supplied for clerks, nurses, nurse practitioners, physicians, and social workers. The client application is being designed using object oriented methodologies and technologies with the C++ programming language, and will operate within a Microsoft Windows operating environment utilizing Object Linking and Embedding for application interoperability.
PMCID: PMC2247750  PMID: 7950000
5.  Complementary use of the SciSearch database for improved biomedical information searching. 
The use of at least two complementary online biomedical databases is generally considered critical for biomedical scientists seeking to keep fully abreast of recent research developments as well as to retrieve the highest number of relevant citations possible. Although the National Library of Medicine's MEDLINE is usually the database of choice, this paper illustrates the benefits of using another database, the Institute for Scientific Information's SciSearch, when conducting a biomedical information search. When a simple query about red wine consumption and coronary artery disease was posed simultaneously in both MEDLINE and SciSearch, a greater number of relevant citations were retrieved through SciSearch. This paper also provides suggestions for carrying out a comprehensive biomedical literature search in a rapid and efficient manner by using SciSearch in conjunction with MEDLINE.
PMCID: PMC226327  PMID: 9549014
6.  Study of Query Expansion Techniques and Their Application in the Biomedical Information Retrieval 
The Scientific World Journal  2014;2014:132158.
Information Retrieval focuses on finding documents whose content matches with a user query from a large document collection. As formulating well-designed queries is difficult for most users, it is necessary to use query expansion to retrieve relevant information. Query expansion techniques are widely applied for improving the efficiency of the textual information retrieval systems. These techniques help to overcome vocabulary mismatch issues by expanding the original query with additional relevant terms and reweighting the terms in the expanded query. In this paper, different text preprocessing and query expansion approaches are combined to improve the documents initially retrieved by a query in a scientific documental database. A corpus belonging to MEDLINE, called Cystic Fibrosis, is used as a knowledge source. Experimental results show that the proposed combinations of techniques greatly enhance the efficiency obtained by traditional queries.
PMCID: PMC3958669  PMID: 24723793
7.  Remote Access MicroMeSH: Demonstration of an Enhanced Microcomputer System for Searching the MEDLINE Database 
Remote Access MicroMeSH (RAMM) is a powerful but easy to use Microcomputer system for searching the medical literature. RAMM uses MicroMeSH, a system for accessing the National Library of Medicine's (NLM) Medical Subject Headings (MeSH) vocabulary, to facilitate off-line creation and refinement of highly specific MEDLINE search queries. Using these queries RAMM automatically searches and retrieves citations from the MEDLINE databases through the National Library of Medicine's (NLM) Medical Literature Analysis and Retrieval System (MEDLARS). As search query creation and citation review are performed off-line the cost of on-line searching in minimized.
PMCID: PMC2245617
8.  Remote Access MicroMeSH: A Microcomputer System for Searching the MEDLINE Database 
This paper describes Remote Access - MicroMeSH (RAMM) a powerful but easy to use microcomputer system for searching the medical literature. RAMM uses MicroMeSH [1], a system for accessing the National Library of Medicine's (NLM) Medical Subject Headings (MeSH) vocabulary, to facilitate off-line creation and refinement of highly specific MEDLINE search queries. Using these queries RAMM automatically searches and retrieves citations from the MEDLINE databases through the National Library of Medicine's (NLM) Medical Literature Analysis and Retrieval System (MEDLARS). RAMM is used by both staff and students at Harvard Medical School. As search query creation and citation review are performed off-line the cost of on-line searching in minimized.
PMCID: PMC2245285
9.  The National Library of Medicine and Medical Informatics 
Western Journal of Medicine  1986;145(6):786-790.
Medical informatics attempts to provide the theoretic and scientific basis for the use of automated information systems in biomedicine. Even though a new field, its roots are in the 19th century. The National Library of Medicine (NLM) began classifying the medical literature and publishing the Index Medicus in 1897; in the early 1960s, the growth of the index gave rise to MEDLARS, the first successful, large-scale, computerized bibliographic system. In 1971, about the time MEDLARS evolved into a nationwide on-line retrieval system known as MEDLINE, a committee of the Association of American Medical Colleges published a report calling for the NLM to exert strong leadership in developing computer applications for information transfer in medicine. The NLM has sponsored several training and research programs in this area and is now developing the concept of “centers of excellence” in medical informatics. In addition, there are a number of current research and development activities within the NLM internal and extramural programs that may influence the progress of medical informatics.
PMCID: PMC1307151  PMID: 3544508
10.  Ranking the whole MEDLINE database according to a large training set using text indexing 
BMC Bioinformatics  2005;6:75.
The MEDLINE database contains over 12 million references to scientific literature, with about 3/4 of recent articles including an abstract of the publication. Retrieval of entries using queries with keywords is useful for human users that need to obtain small selections. However, particular analyses of the literature or database developments may need the complete ranking of all the references in the MEDLINE database as to their relevance to a topic of interest. This report describes a method that does this ranking using the differences in word content between MEDLINE entries related to a topic and the whole of MEDLINE, in a computational time appropriate for an article search query engine.
We tested the capabilities of our system to retrieve MEDLINE references which are relevant to the subject of stem cells. We took advantage of the existing annotation of references with terms from the MeSH hierarchical vocabulary (Medical Subject Headings, developed at the National Library of Medicine). A training set of 81,416 references was constructed by selecting entries annotated with the MeSH term stem cells or some child in its sub tree. Frequencies of all nouns, verbs, and adjectives in the training set were computed and the ratios of word frequencies in the training set to those in the entire MEDLINE were used to score references. Self-consistency of the algorithm, benchmarked with a test set containing the training set and an equal number of references randomly selected from MEDLINE was better using nouns (79%) than adjectives (73%) or verbs (70%). The evaluation of the system with 6,923 references not used for training, containing 204 articles relevant to stem cells according to a human expert, indicated a recall of 65% for a precision of 65%.
This strategy appears to be useful for predicting the relevance of MEDLINE references to a given concept. The method is simple and can be used with any user-defined training set. Choice of the part of speech of the words used for classification has important effects on performance. Lists of words, scripts, and additional information are available from the web address .
PMCID: PMC1274266  PMID: 15790421
11.  Integrating the UMLS into VNS Retriever. 
We are developing a networked resource for the National Library of Medicine's Unified Medical Language System. We call this resource the UMLS Retriever, which is an instance of our VNS Retriever architecture. Our prototype user interface makes use of the Virtual Notebook System Browser. The development of a networked UMLS service will result in numerous advantages to our user community.
PMCID: PMC2248017  PMID: 1482881
12.  Accelerating Best Care at Baylor Dallas 
A culture of quality improvement (QI) is needed to bridge the gap between possible STEEEP™ (safe, timely, effective, efficient, equitable, and patient-centered) care and actual usual care. Baylor Health Care System (BHCS) developed Accelerating Best Care at Baylor (ABC Baylor), an innovative educational program that teaches health care leaders the theory and techniques of rapid-cycle QI. Course participants learn general principles of continuous QI, as well as health care–specific QI techniques, and finish the course by designing and implementing their own QI project. ABC Baylor has been employed in a variety of settings and has spread its success to other organizations, especially small and rural hospitals. These hospitals, like BHCS, have demonstrated sustained improvements that are due in part to the use of ABC Baylor and its reliance on specific modules that focus on health care safety, service, equity, and chronic disease management. The role of ABC Baylor training and consulting is part of the overall culture and infrastructure that have allowed BHCS to achieve success in its improvement journey, including the receipt of several national awards and the achievement of high reliability in compliance with Centers for Medicare and Medicaid Services core measures of processes of care related to heart failure, acute myocardial infarction, community-acquired pneumonia, and surgical care. The culture of rapid-cycle QI facilitated by ABC Baylor serves to link BHCS's vision and goals to practical execution.
PMCID: PMC2760161  PMID: 19865500
13.  Tools for loading MEDLINE into a local relational database 
BMC Bioinformatics  2004;5:146.
Researchers who use MEDLINE for text mining, information extraction, or natural language processing may benefit from having a copy of MEDLINE that they can manage locally. The National Library of Medicine (NLM) distributes MEDLINE in eXtensible Markup Language (XML)-formatted text files, but it is difficult to query MEDLINE in that format. We have developed software tools to parse the MEDLINE data files and load their contents into a relational database. Although the task is conceptually straightforward, the size and scope of MEDLINE make the task nontrivial. Given the increasing importance of text analysis in biology and medicine, we believe a local installation of MEDLINE will provide helpful computing infrastructure for researchers.
We developed three software packages that parse and load MEDLINE, and ran each package to install separate instances of the MEDLINE database. For each installation, we collected data on loading time and disk-space utilization to provide examples of the process in different settings. Settings differed in terms of commercial database-management system (IBM DB2 or Oracle 9i), processor (Intel or Sun), programming language of installation software (Java or Perl), and methods employed in different versions of the software. The loading times for the three installations were 76 hours, 196 hours, and 132 hours, and disk-space utilization was 46.3 GB, 37.7 GB, and 31.6 GB, respectively. Loading times varied due to a variety of differences among the systems. Loading time also depended on whether data were written to intermediate files or not, and on whether input files were processed in sequence or in parallel. Disk-space utilization depended on the number of MEDLINE files processed, amount of indexing, and whether abstracts were stored as character large objects or truncated.
Relational database (RDBMS) technology supports indexing and querying of very large datasets, and can accommodate a locally stored version of MEDLINE. RDBMS systems support a wide range of queries and facilitate certain tasks that are not directly supported by the application programming interface to PubMed. Because there is variation in hardware, software, and network infrastructures across sites, we cannot predict the exact time required for a user to load MEDLINE, but our results suggest that performance of the software is reasonable. Our database schemas and conversion software are publicly available at .
PMCID: PMC524480  PMID: 15471541
14.  Evaluation of the Virus Counter® for rapid baculovirus quantitation 
Journal of virological methods  2010;171(1):111-116.
The utility of a new instrument for rapid virus quantitation, the Virus Counter, was evaluated in a blind study conducted at three sites. This instrument is a substantially improved version of the original academic research instrument described previously by Stoffel et al. (2005a). The addition of hydrodynamic focusing, a self-contained fluidics system and customized software for system control and data analysis has resulted in a commercially viable and available design. Baculovirus samples were provided by Protein Sciences Corporation and blinded to InDevR and Baylor College of Medicine. Protein Sciences Corporation and Baylor College of Medicine analyzed the samples by plaque assay and InDevR analyzed the samples using the Virus Counter. Serial dilution of stock viruses into growth media and buffer allowed for comparison of measured versus intended concentrations. Direct log-scale comparison between pooled Virus Counter results and pooled plaque assay results indicated a linear relationship (slope = 1.1 ± 0.2, R2 = 0.86) with statistically significant Pearson correlation (r = 0.93, p < 0.001).
PMCID: PMC3011032  PMID: 20970458
baculovirus; plaque assay; Virus Counter; recombinant protein; virus quantitation
15.  A Document Clustering and Ranking System for Exploring MEDLINE Citations 
A major problem faced in biomedical informatics involves how best to present information retrieval results. When a single query retrieves many results, simply showing them as a long list often provides poor overview. With a goal of presenting users with reduced sets of relevant citations, this study developed an approach that retrieved and organized MEDLINE citations into different topical groups and prioritized important citations in each group.
A text mining system framework for automatic document clustering and ranking organized MEDLINE citations following simple PubMed queries. The system grouped the retrieved citations, ranked the citations in each cluster, and generated a set of keywords and MeSH terms to describe the common theme of each cluster.
Several possible ranking functions were compared, including citation count per year (CCPY), citation count (CC), and journal impact factor (JIF). We evaluated this framework by identifying as “important” those articles selected by the Surgical Oncology Society.
Our results showed that CCPY outperforms CC and JIF, i.e., CCPY better ranked important articles than did the others. Furthermore, our text clustering and knowledge extraction strategy grouped the retrieval results into informative clusters as revealed by the keywords and MeSH terms extracted from the documents in each cluster.
The text mining system studied effectively integrated text clustering, text summarization, and text ranking and organized MEDLINE retrieval results into different topical groups.
PMCID: PMC1975797  PMID: 17600104
16.  A Scientific Collaboration Tool Built on the Facebook Platform 
We describe an application (“Medline Publications”) written for the Facebook platform that allows users to maintain and publish a list of their own Medline-indexed publications, as well as easily access their contacts’ lists. The system is semi-automatic in that it interfaces directly with the National Library of Medicine’s PubMed database to find and retrieve citation data. Furthermore, the system has the capability to present the user with sets of other users with similar publication profiles. As of July 2008, Medline Publications has attracted approximately 759 users, 624 of which have listed a total of 5,193 unique publications.
PMCID: PMC2656030  PMID: 18999247
17.  Assessing thesaurus-based query expansion using the UMLS Metathesaurus. 
OBJECTIVES: Assess query expansion using thesaurus relationships and definitions in the UMLS Metathesaurus for improving searching performance. METHODS: The queries from a MEDLINE test collection (OHSUMED) were expanded using synonym, hierarchical, and related term information as well as term definitions from the UMLS Metathesaurus. Documents were retrieved from a word-statistical retrieval system and assessed for recall and precision based on relevance judgments from the test collection. RESULTS: All types of query expansion degraded aggregate retrieval performance as measured by recall and precision, although 38.6% of the queries with synonym expansion and up to 29.7% of the queries with hierarchical expansion showed improvement. CONCLUSIONS: Thesaurus-based query expansion causes a decline in retrieval performance generally but improves it in specific instances. Further research must focus on identifying instances where performance improves and how it can be exploited by real users.
PMCID: PMC2244120  PMID: 11079902
18.  Pilot study optimizing MEDLINE queries in an automated disease management telemedicine system. 
Clinicians encounter many medical questions while providing outpatient medical care. A significant number of these questions can be answered using MEDLINE; however it has proven to be difficult to incorporate MEDLINE into routine clinical workflow and for clinicians to generate well constructed MEDLINE queries. This study however hypothesized that that well-constructed MEDLINE queries could be semi-automatically generated by an application named LitButton which was incorporated into the TeleWatch telemedicine system. The LitButton application was then prospectively evaluated in a pilot study by four nurse case managers (NCM) who monitored sixty-eight outpatients for three weeks. During this period the NCMs used the LitButton application sixteen times, and they subjectively reported in real-time that they obtained an answer in 56% of the cases, but that none of the successful information retrieval events resulted in a change in a patient's clinical management. The small number of LitButton events and lack of clinical impact was likely due to the fact that the LitButton function was designed to search MEDLINE for treatment related information; however the NCMs had limited medical decision making responsibilities. As a result there was a mismatch between the user's information needs and the system capabilities.
PMCID: PMC2244362  PMID: 12463918
19.  Investigating CBIR Techniques for Cervicographic Images 
The National Library of Medicine (NLM) and the National Cancer Institute (NCI) are creating a digital archive of 100,000 cervicographic images and clinical and diagnostic data obtained through two major longitudinal studies. In addition to developing tools for Web access to these data, we are conducting research in Content-Based Image Retrieval (CBIR) techniques for retrieving visually similar and pathologically relevant images. The resulting system of tools is expected to greatly benefit medical education and research into uterine cervical cancer which is the second most common cancer affecting women worldwide. Our current prototype system with fundamental CBIR functions operates on a small test subset of images and retrieves relevant cervix images containing tissue regions similar in color, texture, size, and/or location to a query image region marked by the user. Initial average precision result for retrieval by color of acetowhite lesions is 52%, and for the columnar epithelium is 64.2%, respectively.
PMCID: PMC2655825  PMID: 18693952
20.  A Study on Pubmed Search Tag Usage Pattern: Association Rule Mining of a Full-day Pubmed Query Log 
The practice of evidence-based medicine requires efficient biomedical literature search such as PubMed/MEDLINE. Retrieval performance relies highly on the efficient use of search field tags. The purpose of this study was to analyze PubMed log data in order to understand the usage pattern of search tags by the end user in PubMed/MEDLINE search.
A PubMed query log file was obtained from the National Library of Medicine containing anonymous user identification, timestamp, and query text. Inconsistent records were removed from the dataset and the search tags were extracted from the query texts. A total of 2,917,159 queries were selected for this study issued by a total of 613,061 users. The analysis of frequent co-occurrences and usage patterns of the search tags was conducted using an association mining algorithm.
The percentage of search tag usage was low (11.38% of the total queries) and only 2.95% of queries contained two or more tags. Three out of four users used no search tag and about two-third of them issued less than four queries. Among the queries containing at least one tagged search term, the average number of search tags was almost half of the number of total search terms. Navigational search tags are more frequently used than informational search tags. While no strong association was observed between informational and navigational tags, six (out of 19) informational tags and six (out of 29) navigational tags showed strong associations in PubMed searches.
The low percentage of search tag usage implies that PubMed/MEDLINE users do not utilize the features of PubMed/MEDLINE widely or they are not aware of such features or solely depend on the high recall focused query translation by the PubMed’s Automatic Term Mapping. The users need further education and interactive search application for effective use of the search tags in order to fulfill their biomedical information needs from PubMed/MEDLINE.
PMCID: PMC3552776  PMID: 23302604
21.  Challenges in converting an interviewer-administered food probe database to self-administration in the National Cancer Institute Automated Self-administered 24-Hour Recall (ASA24) 
The National Cancer Institute (NCI) is developing an automated, self-administered 24-hour dietary recall (ASA24) application to collect and code dietary intake data. The goal of the ASA24 development is to create a web-based dietary interview based on the US Department of Agriculture (USDA) Automated Multiple Pass Method (AMPM) instrument currently used in the National Health and Nutrition Examination Survey (NHANES). The ASA24 food list, detail probes, and portion probes were drawn from the AMPM instrument; portion-size pictures from Baylor College of Medicine’s Food Intake Recording Software System (FIRSSt) were added; and the food code/portion code assignments were linked to the USDA Food and Nutrient Database for Dietary Studies (FNDDS). The requirements that the interview be self-administered and fully auto-coded presented several challenges as the AMPM probes and responses were linked with the FNDDS food codes and portion pictures. This linking was accomplished through a “food pathway,” or the sequence of steps that leads from a respondent’s initial food selection, through the AMPM probes and portion pictures, to the point at which a food code and gram weight portion size are assigned. The ASA24 interview database that accomplishes this contains more than 1,100 food probes and more than 2 million food pathways and will include about 10,000 pictures of individual foods depicting up to 8 portion sizes per food. The ASA24 will make the administration of multiple days of recalls in large-scale studies economical and feasible.
PMCID: PMC2786178  PMID: 20161418
National Health and Nutrition Examination Survey; NHANES; 24-hour recall; Self-administered 24-hour dietary recall; ASA24; Food portion photograph; AMPM interview; Food data management
22.  Integrating Clinical Medicine into Biomedical Graduate Education to Promote Translational Research: Strategies from Two New PhD Programs 
For several decades, a barrier has existed between research and clinical medicine, making it difficult for aspiring scientists to gain exposure to human pathophysiology and access to clinical/translational research mentors during their graduate training. In 2005, the Howard Hughes Medical Institute announced the Med Into Grad initiative to support graduate programs that integrate clinical knowledge into PhD biomedical training, with the goal of preparing a new cadre of translational researchers to work at the interface of the basic sciences and clinical medicine. Two institutions, Baylor College of Medicine and the Cleveland Clinic/Case Western Reserve University, developed new PhD programs in translational biology and/or molecular medicine. These programs teach the topics and skills that today’s translational researchers must learn as well as expose students to clinical medicine. In this article, the authors compare and contrast the history, implementation, and evaluation of the Translational Biology and Molecular Medicine program at Baylor College of Medicine and the Molecular Medicine program at the Cleveland Clinic/Case Western Reserve University. The authors also demonstrate the feasibility of creating a multidisciplinary graduate program in molecular medicine that integrates pathophysiology and clinical medicine without extending training time. They conclude with a discussion of the similarities in training approaches that exist despite the fact that each program was independently developed and offer observations that emerged during their collaboration that may benefit others who are considering developing similar programs.
PMCID: PMC3529996  PMID: 23165264
23.  Txt2MEDLINE: Text-Messaging Access to MEDLINE/PubMed 
We developed a text messaging system for processing incoming Short Message Service (SMS) queries, retrieving medical journal citations from MEDLINE/PubMed and sending them back to the user in the text message format. A database of medical terminology abbreviations and acronyms was developed to reduce the size of text in journal citations and abstracts because of the 160-character per message limit of text messages. Queries may be sent as full-length terms or abbreviations. An algorithm transforms the citations into the SMS format. An abbreviated TBL (the bottom-line) summary instead of the full abstract is sent to the mobile device to shorten the resulting text. The system decreases citation size by 77.5±7.9%. Txt2MEDLINE provides physicians and healthcare personnel another rapid and convenient method for searching MEDLINE/PubMed through wireless mobile devices. It is accessible from any location worldwide where GSM wireless service is available.
PMCID: PMC1839569  PMID: 17238343
24.  MEDLEARN: a computer-assisted instruction (CAI) program for MEDLARS. 
*MEDLEARN*, a second-generation computer-assisted instruction (CAI) program available (nationally) since October 1976, provides on-line training for MEDLINE, one of the National Library of Medicine's (NLM) Medical Literature Analysis and Retrieval System (MEDLARS) data base. *MEDLEARN* was developed as a joint effort between NLM and The George Washington University Medical Center. Using MEDLINE formats throughout, *MEDLEARN* combines tutorial dialogue, drill and practice, testing, and simulation. The program was designed in three tracks oriented to basic methods, advanced techniques, and new developments. Each topic is presented on two levels, permitting an alternate explanation for users encountering difficulty. *MEDLEARN*, coded in the computer language PILOT, was developed with a modular structure which promotes ease of writing and revision. A versatile control structure maximizes student control. Frequent interactions check immediate recall, general comprehension, and integration of knowledge. Two MEDLINE simulations are included, providing the student an opportunity to formulate and execute a search, have it evaluated, and then perform the search in MEDLINE. Commenting, news broadcasting, and monitoring (with permission only) capabilities are also available. Subjective field appraisals have been positive and NLM plans to expand *MEDLEARN* and produce similar programs for other data bases.
PMCID: PMC225291  PMID: 342015
25.  A pre-search estimation algorithm for MEDLINE strategies with qualifiers. 
Inexperienced users of online medical databases often have difficulty formulating their queries. Systems designed to assist them usually do not estimate how effective the initial search strategy will be before performing an actual search. Consequently, the search may find an overwhelming number of citations, or retrieve nothing at all. We have developed an estimation algorithm to predict the outcome of a MEDLINE search. The portion of the algorithm described here estimates retrieval for strategies containing qualifiers. In test searches, the estimate reduced the trial-and-error of strategy formulation. However, the accuracy of the estimate fell short of expectations. Our results show that pre-search estimation for strategies with qualifiers cannot be performed effectively with only the occurrence data that is presently available. They further imply that automated search intermediaries can benefit from medical knowledge which expresses the relationships that exist between terms.
PMCID: PMC2247864  PMID: 7950056

Results 1-25 (626794)