PubMed and beyond: biomedical literature search in the age of artificial intelligence

Biomedical research yields vast information, much of which is only accessible through the literature. Consequently, literature search is crucial for healthcare and biomedicine. Recent improvements in artificial intelligence (AI) have expanded functionality beyond keywords, but they might be unfamili...

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Vydáno v:EBioMedicine Ročník 100; s. 104988
Hlavní autoři: Jin, Qiao, Leaman, Robert, Lu, Zhiyong
Médium: Journal Article
Jazyk:angličtina
Vydáno: Netherlands Elsevier B.V 01.02.2024
Elsevier
Témata:
Advanced Basic Science
Artificial Intelligence
Biomedical literature search
Biomedical Research
Data Mining
Delivery of Health Care
Humans
Internal Medicine
PubMed
Review
Artificial intelligence
Biomedical literature search
ISSN:2352-3964, 2352-3964
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Shrnutí:Biomedical research yields vast information, much of which is only accessible through the literature. Consequently, literature search is crucial for healthcare and biomedicine. Recent improvements in artificial intelligence (AI) have expanded functionality beyond keywords, but they might be unfamiliar to clinicians and researchers. In response, we present an overview of over 30 literature search tools tailored to common biomedical use cases, aiming at helping readers efficiently fulfill their information needs. We first discuss recent improvements and continued challenges of the widely used PubMed. Then, we describe AI-based literature search tools catering to five specific information needs: 1. Evidence-based medicine. 2. Precision medicine and genomics. 3. Searching by meaning, including questions. 4. Finding related articles with literature recommendation. 5. Discovering hidden associations through literature mining. Finally, we discuss the impacts of recent developments of large language models such as ChatGPT on biomedical information seeking.
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ISSN:2352-3964
2352-3964
DOI:10.1016/j.ebiom.2024.104988