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Diagnostic and Prognostic Research|December 19, 2022
Protocol for development and validation of postpartum cardiovascular disease (CVD) risk prediction model incorporating reproductive and pregnancy-related candidate predictorsSteven Wambua, Francesca Crowe, Shakila Thangaratinam, et al.Diagnostic and Prognostic Research|June 1, 2022
A scoping methodological review of simulation studies comparing statistical and machine learning approaches to risk prediction for time-to-event dataHayley Smith, Michael Sweeting, Tim Morris, et al.Diagnostic and Prognostic Research|May 17, 2019
Prognosis research ideally should measure time-varying predictors at their intended moment of useRebecca Whittle, Kara-Louise Royle, Kelvin P Jordan, et al.Diagnostic and Prognostic Research|May 17, 2019
External validation, update and development of prediction models for pre-eclampsia using an Individual Participant Data (IPD) meta-analysis: the International Prediction of Pregnancy Complication Network (IPPIC pre-eclampsia) protocolJohn Allotey, Kym I E Snell, Claire Chan, et al.Diagnostic and Prognostic Research|May 17, 2019
The Brier score does not evaluate the clinical utility of diagnostic tests or prediction modelsMelissa Assel, Daniel D Sjoberg, Andrew J VickersDiagnostic and Prognostic Research|May 17, 2019
A general approach to risk modeling using partial surrogate markers with application to perioperative acute kidney injuryDerek K Smith, Loren E Smith, Frederic T Billings, et al.Diagnostic and Prognostic Research|May 17, 2019
Quantifying the added value of new biomarkers: how and how notNancy R CookDiagnostic and Prognostic Research|May 17, 2019
Systematic reviews and meta-analyses addressing comparative test accuracy questionsMariska M G Leeflang, Johannes B ReitsmaDiagnostic and Prognostic Research|September 25, 2019
A study protocol for the development and internal validation of a multivariable prognostic model to determine lower extremity muscle injury risk in elite football (soccer) players, with further exploration of prognostic factorsTom Hughes, Richard Riley, Jamie C Sergeant, et al.Diagnostic and Prognostic Research|May 5, 2025
A scoping review of machine learning models to predict risk of falls in elders, without using sensor dataAngelo Capodici, Claudio Fanconi, Catherine Curtin, et al.Pageof 22