| The role of explainability in creating trustworthy artificial intelligence for health care: a comprehensive survey of the terminology, design choices, and evaluation strategies AF Markus, JA Kors, PR Rijnbeek Journal of biomedical informatics 113, 103655, 2021 | 572 | 2021 |
| Trends in the conduct and reporting of clinical prediction model development and validation: a systematic review C Yang, JA Kors, S Ioannou, LH John, AF Markus, A Rekkas, ... Journal of the American Medical Informatics Association 29 (5), 983-989, 2022 | 48 | 2022 |
| Seek COVER: using a disease proxy to rapidly develop and validate a personalized risk calculator for COVID-19 outcomes in an international network RD Williams, AF Markus, C Yang, T Duarte-Salles, SL DuVall, T Falconer, ... BMC Medical Research Methodology 22 (1), 35, 2022 | 48 | 2022 |
| Use of unstructured text in prognostic clinical prediction models: a systematic review TM Seinen, EA Fridgeirsson, S Ioannou, D Jeannetot, LH John, JA Kors, ... Journal of the American Medical Informatics Association 29 (7), 1292-1302, 2022 | 46 | 2022 |
| Assessing trustworthy AI in times of COVID-19: deep learning for predicting a multiregional score conveying the degree of lung compromise in COVID-19 patients H Allahabadi, J Amann, I Balot, A Beretta, C Binkley, J Bozenhard, ... IEEE Transactions on Technology and Society 3 (4), 272-289, 2022 | 21 | 2022 |
| Implementation of the COVID-19 vulnerability index across an international network of health care data sets: collaborative external validation study JM Reps, C Kim, RD Williams, AF Markus, C Yang, T Duarte-Salles, ... JMIR medical informatics 9 (4), e21547, 2021 | 19 | 2021 |
| Seek COVER: development and validation of a personalized risk calculator for COVID-19 outcomes in an international network. medRxiv 2020 RD Williams, AF Markus, C Yang, TD Salles, T Falconer, J Jonnagaddala, ... Clinical infectious diseases: an oficial publication of the Infectious …, 2020 | 11 | 2020 |
| Can we trust the prediction model? Demonstrating the importance of external validation by investigating the COVID-19 Vulnerability (C-19) Index across an international network … JM Reps, C Kim, RD Williams, AF Markus, C Yang, TD Salles, T Falconer, ... medRxiv, 2020.06. 15.20130328, 2020 | 9 | 2020 |
| Does competition improve hospital performance: a DEA based evaluation from the Netherlands P Dohmen, M van Ineveld, A Markus, L van der Hagen, J van de Klundert The European Journal of Health Economics 24 (6), 999-1017, 2023 | 8 | 2023 |
| TreatmentPatterns: an R package to facilitate the standardized development and analysis of treatment patterns across disease domains AF Markus, KMC Verhamme, JA Kors, PR Rijnbeek Computer Methods and Programs in Biomedicine 225, 107081, 2022 | 6 | 2022 |
| Eliminating transplant waiting time inequities–With an application to kidney allocation in the USA J Van de Klundert, L van der Hagen, A Markus European Journal of Operational Research 297 (3), 977-985, 2022 | 4 | 2022 |
| Characterising the treatment of thromboembolic events after COVID-19 vaccination in 4 European countries and the US: An international network cohort study AF Markus, VY Strauss, E Burn, X Li, A Delmestri, C Reich, C Yin, ... Frontiers in Pharmacology 14, 1118203, 2023 | 2 | 2023 |
| Real-world treatment trajectories of adults with newly diagnosed asthma or COPD AF Markus, PR Rijnbeek, JA Kors, E Burn, T Duarte-Salles, M Haug, ... BMJ Open Respiratory Research 11 (1), e002127, 2024 | 1 | 2024 |
| Semantic meaningfulness: Evaluating counterfactual approaches for real-world plausibility and feasibility J Höllig, AF Markus, J de Slegte, P Bagave World Conference on Explainable Artificial Intelligence, 636-659, 2023 | 1 | 2023 |
| Understanding the Size of the Feature Importance Disagreement Problem in Real-World Data AF Markus, EA Fridgeirsson, JA Kors, KMC Verhamme, JM Reps, ... ICML 3rd Workshop on Interpretable Machine Learning in Healthcare (IMLH), 2023 | 1 | 2023 |
| Why predicting risk can’t identify ‘risk factors’: empirical assessment of model stability in machine learning across observational health databases AF Markus, PR Rijnbeek, JM Reps Machine Learning for Healthcare Conference, 828-852, 2022 | 1 | 2022 |
| TreatmentPatterns: An R package to analyze treatment patterns of a study population of interest AF Markus, KMC Verhamme, JA Kors, PR Rijnbeek medRxiv, 2022.01. 24.22269588, 2022 | 1 | 2022 |
| Trends in the development and validation of patient-level prediction models using electronic health record data: a systematic review C Yang, JA Kors, S Ioannou, LH John, AF Markus, A Rekkas, M de Ridder, ... | 1 | 2015 |
| Challenges of Estimating Global Feature Importance in Real-World Health Care Data AF Markus, EA Fridgeirsson, JA Kors, K Verhamme, PR Rijnbeek Caring is Sharing–Exploiting the Value in Data for Health and Innovation …, 2023 | | 2023 |
| Real-world treatment patterns of newly diagnosed patients with asthma and/or COPD A Markus, P Rijnbeek, J Kors, G Brusselle, E Burn, D Prieto-Alhambra, ... European Respiratory Journal 58 (suppl 65), 2021 | | 2021 |
