The role of patient-reported outcome measures in trials of artificial intelligence health technologies: a systematic evaluation of ClinicalTrials.gov records (1997

The role of patient-reported outcome measures in trials of artificial intelligence health technologies: a systematic evaluation of ClinicalTrials.gov records (1997–2022)

Published:2023-03 Issue:3 Volume:5 Page:e160-e167
ISSN:2589-7500
Container-title:The Lancet Digital Health
language:en
Short-container-title:The Lancet Digital Health

Author:

Pearce Finlay J,Cruz Rivera Samantha,Liu Xiaoxuan,Manna Elaine,Denniston Alastair K,Calvert Melanie J

Funder

University of Birmingham

Publisher

Elsevier BV

Subject

Health Information Management,Decision Sciences (miscellaneous),Health Informatics,Medicine (miscellaneous)

Reference34 articles.

1. The AI Index 2022 annual report. AI Index Steering Committee, Stanford Institute for Human-Centered AI;Zhang,2022

2. The practical implementation of artificial intelligence technologies in medicine;He;Nat Med,2019

3. High-performance medicine: the convergence of human and artificial intelligence;Topol;Nat Med,2019

4. Improving proteinuria screening with mailed smartphone urinalysis testing in previously unscreened patients with hypertension: a randomized controlled trial;Leddy;BMC Nephrol,2019

5. Patient reported outcome measures could help transform healthcare;Black;BMJ,2013

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