Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): The TRIPOD Statement G Collins, J Reitsma, D Altman, K Moons Annals of Internal Medicine 162 (1), 55-63, 2015 | 8203 | 2015 |
Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration KGM Moons, DG Altman, JB Reitsma, JPA Ioannidis, P Macaskill, ... Annals of internal medicine 162 (1), W1-W73, 2015 | 3915 | 2015 |
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 | 3126 | 2020 |
PROBAST: a tool to assess the risk of bias and applicability of prediction model studies RF Wolff, KGM Moons, RD Riley, PF Whiting, M Westwood, GS Collins, ... Annals of internal medicine 170 (1), 51-58, 2019 | 1427 | 2019 |
A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models E Christodoulou, J Ma, GS Collins, EW Steyerberg, JY Verbakel, ... Journal of clinical epidemiology 110, 12-22, 2019 | 1380 | 2019 |
Critical appraisal and data extraction for systematic reviews of prediction modelling studies: the CHARMS checklist KGM Moons, JAH de Groot, W Bouwmeester, Y Vergouwe, S Mallett, ... PLoS medicine 11 (10), e1001744, 2014 | 1348 | 2014 |
Calculating the sample size required for developing a clinical prediction model RD Riley, J Ensor, KIE Snell, FE Harrell, GP Martin, JB Reitsma, ... Bmj 368, 2020 | 1274 | 2020 |
Guidelines for accurate and transparent health estimates reporting: the GATHER statement GA Stevens, L Alkema, RE Black, JT Boerma, GS Collins, M Ezzati, ... The Lancet 388 (10062), e19-e23, 2016 | 1235 | 2016 |
PROBAST: a tool to assess risk of bias and applicability of prediction model studies: explanation and elaboration KGM Moons, RF Wolff, RD Riley, PF Whiting, M Westwood, GS Collins, ... Annals of internal medicine 170 (1), W1-W33, 2019 | 927 | 2019 |
Global, regional and national burden of osteoarthritis 1990-2017: a systematic analysis of the Global Burden of Disease Study 2017 S Safiri, AA Kolahi, E Smith, C Hill, D Bettampadi, MA Mansournia, D Hoy, ... Annals of the rheumatic diseases 79 (6), 819-828, 2020 | 916 | 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, 2016 | 817 | 2016 |
Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension X Liu, SC Rivera, D Moher, MJ Calvert, AK Denniston, H Ashrafian, ... The Lancet Digital Health 2 (10), e537-e548, 2020 | 750 | 2020 |
Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies M Nagendran, Y Chen, CA Lovejoy, AC Gordon, M Komorowski, ... bmj 368, 2020 | 745 | 2020 |
Selection of single blastocysts for fresh transfer via standard morphology assessment alone and with array CGH for good prognosis IVF patients: results from a randomized pilot … Z Yang, J Liu, GS Collins, SA Salem, X Liu, SS Lyle, AC Peck, ES Sills, ... Molecular cytogenetics 5, 1-8, 2012 | 719 | 2012 |
Minimum sample size for developing a multivariable prediction model: PART II‐binary and time‐to‐event outcomes RD Riley, KIE Snell, J Ensor, DL Burke, FE Harrell Jr, KGM Moons, ... Statistics in medicine 38 (7), 1276-1296, 2019 | 717 | 2019 |
External validation of multivariable prediction models: a systematic review of methodological conduct and reporting GS Collins, JA de Groot, S Dutton, O Omar, M Shanyinde, A Tajar, ... BMC medical research methodology 14, 1-11, 2014 | 679 | 2014 |
Global, regional and national burden of rheumatoid arthritis 1990–2017: a systematic analysis of the Global Burden of Disease study 2017 S Safiri, AA Kolahi, D Hoy, E Smith, D Bettampadi, MA Mansournia, ... Annals of the rheumatic diseases 78 (11), 1463-1471, 2019 | 661 | 2019 |
Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension SC Rivera, X Liu, AW Chan, AK Denniston, MJ Calvert, H Ashrafian, ... The Lancet Digital Health 2 (10), e549-e560, 2020 | 637 | 2020 |
Reporting of artificial intelligence prediction models GS Collins, KGM Moons The Lancet 393 (10181), 1577-1579, 2019 | 584 | 2019 |
Sample size considerations for the external validation of a multivariable prognostic model: a resampling study GS Collins, EO Ogundimu, DG Altman Statistics in medicine 35 (2), 214-226, 2016 | 564 | 2016 |