Machine learning and artificial intelligence research for patient benefit: 20 critical questions on...
Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness
About this item
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Author / Creator
Vollmer, Sebastian , Mateen, Bilal A , Bohner, Gergo , Király, Franz J , Ghani, Rayid , Jonsson, Pall , Cumbers, Sarah , Jonas, Adrian , McAllister, Katherine S L , Myles, Puja , Grainger, David , Birse, Mark , Branson, Richard , Moons, Karel G M , Collins, Gary S , Ioannidis, John P A , Holmes, Chris and Hemingway, Harry
Publisher
England: British Medical Journal Publishing Group
Journal title
Language
English
Formats
Publication information
Publisher
England: British Medical Journal Publishing Group
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Scope and Contents
Contents
Machine learning, artificial intelligence, and other modern statistical methods are providing new opportunities to operationalise previously untapped and rapidly growing sources of data for patient benefit. Despite much promising research currently being undertaken, particularly in imaging, the literature as a whole lacks transparency, clear report...
Alternative Titles
Full title
Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness
Authors, Artists and Contributors
Author / Creator
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Primary Identifiers
Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11515850
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11515850
Other Identifiers
ISSN
1756-1833,0959-8138
E-ISSN
1756-1833
DOI
10.1136/bmj.l6927
