Machine learning models for abstract screening task - A systematic literature review application for health economics and outcome research

Objective Systematic literature reviews (SLRs) are critical for life-science research. However, the manual selection and retrieval of relevant publications can be a time-consuming process. This study aims to (1) develop two disease-specific annotated corpora, one for human papillomavirus (HPV) assoc...

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Vydáno v:	BMC medical research methodology Ročník 24; číslo 1; s. 108 - 7
Hlavní autoři:	Du, Jingcheng, Soysal, Ekin, Wang, Dong, He, Long, Lin, Bin, Wang, Jingqi, Manion, Frank J., Li, Yeran, Wu, Elise, Yao, Lixia
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London BioMed Central 09.05.2024 BioMed Central Ltd Springer Nature B.V BMC
Témata:	Abstracting and Indexing - methods Algorithms Application programming interface Article screening Automation Bibliographic data bases Classification Cost control Deep Learning Economics, Medical Evaluation Health economics Health Sciences Human papillomavirus Humans Keywords Literature reviews Machine Learning Medical economics Medical research Medical screening Medicine Medicine & Public Health Medicine, Experimental Metadata Methods Natural language Outcome Assessment, Health Care - methods Papillomavirus Infections - diagnosis Pediatrics R&D Regression analysis Research & development Statistical Theory and Methods Statistics for Life Sciences Subject specialists Support vector machines Systematic literature review Text categorization Text classification Theory of Medicine/Bioethics Treatment outcome United States Deep learning Article screening Machine learning Text classification Systematic literature review
ISSN:	1471-2288, 1471-2288
On-line přístup:	Získat plný text
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