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For: Levis B, Snell KIE, Damen JAA, Hattle M, Ensor J, Dhiman P, Andaur Navarro CL, Takwoingi Y, Whiting PF, Debray TPA, Reitsma JB, Moons KGM, Collins GS, Riley RD. Risk of bias assessments in individual participant data meta-analyses of test accuracy and prediction models: a review shows improvements are needed. J Clin Epidemiol 2024;165:111206. [PMID: 37925059 DOI: 10.1016/j.jclinepi.2023.10.022] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 10/19/2023] [Accepted: 10/30/2023] [Indexed: 11/06/2023]
Number Cited by Other Article(s)
1
Lyman GH, Kuderer NM. Artificial Intelligence in Cancer Clinical Research: II. Development and Validation of Clinical Prediction Models. Cancer Invest 2024;42:447-451. [PMID: 38775011 DOI: 10.1080/07357907.2024.2354991] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/13/2024]
2
Costa AF, McInnes MDF, van der Pol CB, Lam E, Dawit H, Salameh JP, Levis B, Bashir MR. Individual Participant Data Meta-Analyses for Diagnostic Accuracy Research: Challenges and Lessons Learned from the LI-RADS IPD Group. Radiol Imaging Cancer 2024;6:e240015. [PMID: 38578208 PMCID: PMC11148817 DOI: 10.1148/rycan.240015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Revised: 02/20/2024] [Accepted: 02/27/2024] [Indexed: 04/06/2024]
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