| Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal L Wynants, B Van Calster, GS Collins, RD Riley, G Heinze, E Schuit, ... bmj 369, 2020 | 3334 | 2020 |
| Prediction models for cardiovascular disease risk in the general population: systematic review JAAG Damen, L Hooft, E Schuit, TPA Debray, GS Collins, I Tzoulaki, ... bmj 353, i2416, 2016 | 908 | 2016 |
| A guide to systematic review and meta-analysis of prognostic factor studies RD Riley, KGM Moons, KIE Snell, J Ensor, L Hooft, DG Altman, J Hayden, ... bmj 364, k4597, 2019 | 600 | 2019 |
| A new framework to enhance the interpretation of external validation studies of clinical prediction models TPA Debray, Y Vergouwe, H Koffijberg, D Nieboer, EW Steyerberg, ... Journal of clinical epidemiology 68 (3), 279-289, 2015 | 568 | 2015 |
| External validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis: opportunities and challenges RD Riley, J Ensor, KIE Snell, TPA Debray, DG Altman, KGM Moons, ... bmj 353, i3140, 2016 | 526 | 2016 |
| Prognosis for patients with amyotrophic lateral sclerosis: development and validation of a personalised prediction model HJ Westeneng, TPA Debray, AE Visser, RPA van Eijk, JPK Rooney, ... The Lancet Neurology 17 (5), 423-433, 2018 | 507 | 2018 |
| A guide to systematic review and meta-analysis of prediction model performance TPA Debray, JAAG Damen, KIE Snell, J Ensor, L Hooft, JB Reitsma, ... bmj 356, i6460, 2017 | 501 | 2017 |
| GetReal in network meta‐analysis: a review of the methodology O Efthimiou, TPA Debray, G van Valkenhoef, S Trelle, K Panayidou, ... Research synthesis methods 7 (3), 236-263, 2016 | 344 | 2016 |
| Get real in individual participant data (IPD) meta‐analysis: a review of the methodology TPA Debray, KGM Moons, G van Valkenhoef, O Efthimiou, N Hummel, ... Research synthesis methods 6 (4), 293-309, 2015 | 341 | 2015 |
| Guidelines and quality criteria for artificial intelligence-based prediction models in healthcare: a scoping review AAH de Hond, AM Leeuwenberg, L Hooft, IMJ Kant, SWJ Nijman, ... npj Digital Medicine 5 (1), 1-13, 2022 | 320 | 2022 |
| Minimum sample size for external validation of a clinical prediction model with a binary outcome RD Riley, TPA Debray, GS Collins, L Archer, J Ensor, M van Smeden, ... Statistics in Medicine 40 (19), 4230-4251, 2021 | 237 | 2021 |
| A framework for developing, implementing, and evaluating clinical prediction models in an individual participant data meta‐analysis T Debray, KGM Moons, I Ahmed, H Koffijberg, RD Riley Statistics in medicine 32 (18), 3158-3180, 2013 | 221 | 2013 |
| Individual participant data meta-analysis for a binary outcome: one-stage or two-stage? TPA Debray, KGM Moons, GMA Abo-Zaid, H Koffijberg, RD Riley PloS one 8 (4), e60650, 2013 | 219 | 2013 |
| Performance of the Framingham risk models and pooled cohort equations for predicting 10-year risk of cardiovascular disease: a systematic review and meta-analysis JA Damen, R Pajouheshnia, P Heus, KGM Moons, JB Reitsma, ... BMC medicine 17 (1), 1-16, 2019 | 195 | 2019 |
| A framework for meta-analysis of prediction model studies with binary and time-to-event outcomes TPA Debray, JAAG Damen, RD Riley, K Snell, JB Reitsma, L Hooft, ... Statistical methods in medical research 28 (9), 2768-2786, 2019 | 194 | 2019 |
| Imputation of systematically missing predictors in an individual participant data meta‐analysis: a generalized approach using MICE S Jolani, TPA Debray, H Koffijberg, S van Buuren, KGM Moons Statistics in medicine 34 (11), 1841-1863, 2015 | 191 | 2015 |
| Detecting small‐study effects and funnel plot asymmetry in meta‐analysis of survival data: A comparison of new and existing tests TPA Debray, KGM Moons, RD Riley Research synthesis methods 9 (1), 41-50, 2018 | 177 | 2018 |
| Combining randomized and non‐randomized evidence in network meta‐analysis O Efthimiou, D Mavridis, TPA Debray, M Samara, M Belger, GCM Siontis, ... Statistics in medicine 36 (8), 1210-1226, 2017 | 172 | 2017 |
| Multiple imputation for multilevel data with continuous and binary variables V Audigier, IR White, S Jolani, TPA Debray, M Quartagno, J Carpenter, ... Statistical Science 33 (2), 160-183, 2018 | 167 | 2018 |
| Missing data is poorly handled and reported in prediction model studies using machine learning: a literature review SWJ Nijman, AM Leeuwenberg, I Beekers, I Verkouter, JJL Jacobs, ... Journal of clinical epidemiology 142, 218-229, 2022 | 156 | 2022 |
Richard D RileyUniversity of Birmingham, UK.確認したメール アドレス: bham.ac.uk