| 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, 2020 | 3305 | 2020 |
| Calculating the sample size required for developing a clinical prediction model RD Riley, J Ensor, KIE Snell, FE Harrell, GP Martin, JB Reitsma, ... BMJ, 2020 | 1531 | 2020 |
| Calibration: the Achilles heel of predictive analytics B Van Calster, DJ McLernon, M van Smeden, L Wynants, EW Steyerberg BMC medicine 17 (1), 1-7, 2019 | 1161 | 2019 |
| Sample size for binary logistic prediction models: beyond events per variable criteria M van Smeden, KGM Moons, JAH de Groot, GS Collins, DG Altman, ... Statistical methods in medical research 28 (8), 2455-2474, 2019 | 579 | 2019 |
| Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial … GS Collins, P Dhiman, CLA Navarro, J Ma, L Hooft, JB Reitsma, P Logullo, ... BMJ open 11 (7), e048008, 2021 | 522 | 2021 |
| No rationale for 1 variable per 10 events criterion for binary logistic regression analysis M van Smeden, JAH de Groot, KGM Moons, GS Collins, DG Altman, ... BMC medical research methodology 16 (1), 1-12, 2016 | 490 | 2016 |
| 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 | 273 | 2022 |
| Metrics reloaded: Pitfalls and recommendations for image analysis validation L Maier-Hein, B Menze arXiv. org, 2022 | 263* | 2022 |
| Development and validation of the ISARIC 4C Deterioration model for adults hospitalised with COVID-19: a prospective cohort study RK Gupta, EM Harrison, A Ho, AB Docherty, SR Knight, M van Smeden, ... The Lancet respiratory medicine, 2021 | 237 | 2021 |
| Latent class models in diagnostic studies when there is no reference standard—a systematic review M van Smeden, CA Naaktgeboren, JB Reitsma, KGM Moons, ... American journal of epidemiology 179 (4), 423-431, 2014 | 229 | 2014 |
| Systematic evaluation and external validation of 22 prognostic models among hospitalised adults with COVID-19: An observational cohort study RK Gupta, M Marks, THA Samuels, A Luintel, T Rampling, H Chowdhury, ... European respiratory journal, 2020 | 227 | 2020 |
| Time to reality check the promises of machine learning-powered precision medicine J Wilkinson, KF Arnold, EJ Murray, M van Smeden, K Carr, R Sippy, ... The Lancet digital health, 2020 | 220 | 2020 |
| 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, 2021 | 211 | 2021 |
| Common limitations of image processing metrics: A picture story A Reinke, MD Tizabi, CH Sudre, M Eisenmann, T Rädsch, M Baumgartner, ... arXiv preprint arXiv:2104.05642, 2021 | 185 | 2021 |
| Cardiac complications in patients hospitalised with COVID-19 M Linschoten, S Peters, M van Smeden, LS Jewbali, J Schaap, ... European heart journal: acute cardiovascular care 9 (8), 817-823, 2020 | 168 | 2020 |
| TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods GS Collins, KGM Moons, P Dhiman, RD Riley, AL Beam, B Van Calster, ... bmj 385, 2024 | 160 | 2024 |
| The harm of class imbalance corrections for risk prediction models: illustration and simulation using logistic regression R Goorbergh, M van Smeden, D Timmerman, B Van Calster Journal of the American medical informatics association, 2022 | 157 | 2022 |
| Reflection on modern methods: five myths about measurement error in epidemiological research M van Smeden, TL Lash, RHH Groenwold International journal of epidemiology 49 (1), 338-347, 2020 | 150 | 2020 |
| Three myths about risk thresholds for prediction models L Wynants, M Van Smeden, DJ McLernon, D Timmerman, EW Steyerberg, ... BMC medicine 17, 1-7, 2019 | 143 | 2019 |
| Sample size considerations and predictive performance of multinomial logistic prediction models VMT de Jong, MJC Eijkemans, B van Calster, D Timmerman, KGM Moons, ... Statistics in medicine 38 (9), 1601-1619, 2019 | 143 | 2019 |
Ben Van CalsterProfessor of Medical Statistics, KU LeuvenEmail verificata su kuleuven.be