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Machine Learning (1501) Natural Language Processing (706) Decision Support for Health Professionals (1210) Information Retrieval (296) Artificial Intelligence (1421) Epublishing and Open Access (86) Knowledge Translation and Implementation Science (407)

Published on in Vol 9, No 9 (2021): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/30401, first published .
Machine Learning Approaches to Retrieve High-Quality, Clinically Relevant Evidence From the Biomedical Literature: Systematic Review

Machine Learning Approaches to Retrieve High-Quality, Clinically Relevant Evidence From the Biomedical Literature: Systematic Review

Machine Learning Approaches to Retrieve High-Quality, Clinically Relevant Evidence From the Biomedical Literature: Systematic Review

Authors of this article:

Wael Abdelkader1 Author Orcid Image ;   Tamara Navarro1 Author Orcid Image ;   Rick Parrish1 Author Orcid Image ;   Chris Cotoi1 Author Orcid Image ;   Federico Germini1, 2 Author Orcid Image ;   Alfonso Iorio1, 2 Author Orcid Image ;   R Brian Haynes1, 2 Author Orcid Image ;   Cynthia Lokker1 Author Orcid Image
Article Authors Cited by (18) Tweetations (9) Metrics

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  2. Yang X, Mu D, Peng H, Li H, Wang Y, Wang P, Wang Y, Han S. Research and Application of Artificial Intelligence Based on Electronic Health Records of Patients With Cancer: Systematic Review. JMIR Medical Informatics 2022;10(4):e33799 View
  3. Weimer K, Buschhart C, Broelz E, Enck P, Horing B. Bibliometric Properties of Placebo Literature From the JIPS Database: A Descriptive Study. Frontiers in Psychiatry 2022;13 View
  4. Abdelkader W, Navarro T, Parrish R, Cotoi C, Germini F, Linkins L, Iorio A, Haynes R, Ananiadou S, Chu L, Lokker C. A Deep Learning Approach to Refine the Identification of High-Quality Clinical Research Articles From the Biomedical Literature: Protocol for Algorithm Development and Validation. JMIR Research Protocols 2021;10(11):e29398 View
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  7. Hocking L, Parkinson S, Adams A, Molding Nielsen E, Ang C, de Carvalho Gomes H. Overcoming the challenges of using automated technologies for public health evidence synthesis. Eurosurveillance 2023;28(45) View
  8. Mehrabanian M, Eskandari-Yaghbastlo A. The role of AI in advancing evidence-based dentistry. Dental Update 2024;51(1):66 View
  9. Sivarajkumar S, Kelley M, Samolyk-Mazzanti A, Visweswaran S, Wang Y. An Empirical Evaluation of Prompting Strategies for Large Language Models in Zero-Shot Clinical Natural Language Processing: Algorithm Development and Validation Study. JMIR Medical Informatics 2024;12:e55318 View
  10. Tóth B, Berek L, Gulácsi L, Péntek M, Zrubka Z. Automation of systematic reviews of biomedical literature: a scoping review of studies indexed in PubMed. Systematic Reviews 2024;13(1) View
  11. Lokker C, McKibbon K, Afzal M, Navarro T, Linkins L, Haynes R, Iorio A. The McMaster Health Information Research Unit: Over a Quarter-Century of Health Informatics Supporting Evidence-Based Medicine. Journal of Medical Internet Research 2024;26:e58764 View
  12. Komoda D, Cardoso M, Fernandes B, Visacri M, Correa C. Artificial intelligence applied in human health technology assessment: a scoping review protocol. JBI Evidence Synthesis 2024;22(12):2559 View
  13. Lokker C, Abdelkader W, Bagheri E, Parrish R, Cotoi C, Navarro T, Germini F, Linkins L, Haynes R, Chu L, Afzal M, Iorio A, McGinnis R. Boosting efficiency in a clinical literature surveillance system with LightGBM. PLOS Digital Health 2024;3(9):e0000299 View
  14. Fang Z, Arana-Catania M, van Lier F, Outes Velarde J, Bregazzi H, Airoldi M, Carter E, Procter R. SyROCCo: enhancing systematic reviews using machine learning. Data & Policy 2024;6 View

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