ArticleJournal of the American Medical Informatics Association : JAMIA
Knowledge-based methods to help clinicians find answers in MEDLINE.
Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed.
- Retrieval augmented scientific claim verification.JAMIA open · 2024Article
- Examining the role of MEDLINE as a patient care information resource: an analysis of data from the Value of Libraries study.Journal of the Medical Library Association : JMLA · 2017Article
- Integrating unified medical language system and association mining techniques into relevance feedback for biomedical literature search.BMC bioinformatics · 2016Article
- Automated identification of molecular effects of drugs (AIMED).Journal of the American Medical Informatics Association : JAMIA · 2016Article
- SimQ: real-time retrieval of similar consumer health questions.Journal of medical Internet research · 2015Article
- NCBO Resource Index: Ontology-Based Search and Mining of Biomedical Resources.Web semantics (Online) · 2011Article
- Collaborative search in electronic health records.Journal of the American Medical Informatics Association : JAMIA · 2011Article
- AskHERMES: An online question answering system for complex clinical questions.Journal of biomedical informatics · 2011Article
- Effectiveness of lexico-syntactic pattern matching for ontology enrichment with clinical documents.Methods of information in medicine · 2011Article
- Automatically extracting information needs from complex clinical questions.Journal of biomedical informatics · 2010Article
- Enabling multi-level relevance feedback on PubMed by integrating rank learning into DBMS.BMC bioinformatics · 2010Article
- Ontology-driven indexing of public datasets for translational bioinformatics.BMC bioinformatics · 2009Article
- Comparison of ontology-based semantic-similarity measures.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2008Article
- Semantic processing to support clinical guideline development.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2008Article
- Linking genes to literature: text mining, information extraction, and retrieval applications for biology.Genome biology · 2008Review
- Biomedical ontologies in action: role in knowledge management, data integration and decision support.Yearbook of medical informatics · 2008Article
- Voice capture of medical residents' clinical information needs during an inpatient rotation.Journal of the American Medical Informatics Association : JAMIAArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
objectivesLarge databases of published medical research can support clinical decision making by providing physicians with the best available evidence. The time required to obtain optimal results from these databases using traditional systems often makes accessing the databases impractical for clinicians. This article explores whether a hybrid approach of augmenting traditional information retrieval with knowledge-based methods facilitates finding practical clinical advice in the research literature.
designThree experimental systems were evaluated for their ability to find MEDLINE citations providing answers to clinical questions of different complexity. The systems (SemRep, Essie, and CQA-1.0), which rely on domain knowledge and semantic processing to varying extents, were evaluated separately and in combination. Fifteen therapy and prevention questions in three categories (general, intermediate, and specific questions) were searched. The first 10 citations retrieved by each system were randomized, anonymized, and evaluated on a three-point scale. The reasons for ratings were documented. MEASUREMENTS: Metrics evaluating the overall performance of a system (mean average precision, binary preference) and metrics evaluating the number of relevant documents in the first several presented to a physician were used.
resultsScores (mean average precision = 0.57, binary preference = 0.71) for fusion of the retrieval results of the three systems are significantly (p < 0.01) better than those for any individual system. All three systems present three to four relevant citations in the first five for any question type.
conclusionThe improvements in finding relevant MEDLINE citations due to knowledge-based processing show promise in assisting physicians to answer questions in clinical practice.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.