| Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness S Vollmer*, BA Mateen*, G Bohner, FJ Király, R Ghani, P Jonsson, ... BMJ 368, 2020 | 486* | 2020 |
| Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI B Vasey, M Nagendran, B Campbell, DA Clifton, GS Collins, S Denaxas, ... BMJ 377, 2022 | 411 | 2022 |
| 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 | 308 | 2024 |
| Improving survival of critical care patients with coronavirus disease 2019 in England: a national cohort study, March to June 2020 JM Dennis, AP McGovern, SJ Vollmer, BA Mateen Critical Care Medicine, 2020 | 238 | 2020 |
| Type 2 diabetes and COVID-19–related mortality in the critical care setting: a national cohort study in England, March–July 2020 JM Dennis, BA Mateen, R Sonabend, NJ Thomas, KA Patel, AT Hattersley, ... Diabetes care 44 (1), 50-57, 2021 | 209 | 2021 |
| Developing a reporting guideline for artificial intelligence-centred diagnostic test accuracy studies: the STARD-AI protocol V Sounderajah, H Ashrafian, RM Golub, S Shetty, J De Fauw, L Hooft, ... BMJ open 11 (6), e047709, 2021 | 198 | 2021 |
| A quality assessment tool for artificial intelligence-centered diagnostic test accuracy studies: QUADAS-AI V Sounderajah, H Ashrafian, S Rose, NH Shah, M Ghassemi, R Golub, ... Nature medicine 27 (10), 1663-1665, 2021 | 132 | 2021 |
| The value of standards for health datasets in artificial intelligence-based applications A Arora, JE Alderman, J Palmer, S Ganapathi, E Laws, MD Mccradden, ... Nature Medicine 29 (11), 2929-2938, 2023 | 107 | 2023 |
| Improving the quality of machine learning in health applications and clinical research BA Mateen, J Liley, AK Denniston, CC Holmes, SJ Vollmer Nature Machine Intelligence 2 (10), 554-556, 2020 | 76 | 2020 |
| Digital health management during and beyond the COVID-19 pandemic: Opportunities, barriers, and recommendations B Inkster, R O’Brien, E Selby, S Joshi, V Subramanian, M Kadaba, ... JMIR Mental Health 7 (7), e19246, 2020 | 75* | 2020 |
| COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records JH Thygesen, C Tomlinson, S Hollings, MA Mizani, A Handy, A Akbari, ... The Lancet Digital Health 4 (7), e542-e557, 2022 | 72* | 2022 |
| Tackling bias in AI health datasets through the STANDING Together initiative S Ganapathi, J Palmer, JE Alderman, M Calvert, C Espinoza, J Gath, ... Nature Medicine 28 (11), 2232-2233, 2022 | 63 | 2022 |
| The association between mechanical ventilator compatible bed occupancy and mortality risk in intensive care patients with COVID-19: a national retrospective cohort study H Wilde, T Mellan, I Hawryluk, JM Dennis, S Denaxas, C Pagel, A Duncan, ... BMC medicine 19, 1-12, 2021 | 54 | 2021 |
| Hospital bed capacity and usage across secondary healthcare providers in England during the first wave of the COVID-19 pandemic: a descriptive analysis BA Mateen, H Wilde, JM Dennis, A Duncan, N Thomas, A McGovern, ... BMJ open 11 (1), e042945, 2021 | 53* | 2021 |
| Early Warning Signs of a Mental Health Tsunami: A Coordinated Response to Gather Initial Data Insights From Multiple Digital Services Providers B Inkster, DMHDI Group Frontiers in Digital Health 2, 578902, 2021 | 49* | 2021 |
| The Trail Making test: a study of its ability to predict falls in the acute neurological in-patient population BA Mateen, M Bussas, C Doogan, D Waller, A Saverino, FJ Király, ... Clinical rehabilitation 32 (10), 1396-1405, 2018 | 37* | 2018 |
| DNA methylation: basic biology and application to traumatic brain injury BA Mateen, CS Hill, SC Biddie, DK Menon Journal of neurotrauma 34 (16), 2379-2388, 2017 | 36 | 2017 |
| Development of a treatment selection algorithm for SGLT2 and DPP-4 inhibitor therapies in people with type 2 diabetes: a retrospective cohort study JM Dennis, KG Young, AP McGovern, BA Mateen, SJ Vollmer, ... The Lancet Digital Health 4 (12), e873-e883, 2022 | 35* | 2022 |
| Validation framework for the use of AI in healthcare: overview of the new British standard BS30440 M Sujan, C Smith-Frazer, C Malamateniou, J Connor, A Gardner, ... BMJ Health & Care Informatics 30 (1), 2023 | 28 | 2023 |
| The disproportionate excess mortality risk of COVID-19 in younger people with diabetes warrants vaccination prioritisation AP McGovern, NJ Thomas, SJ Vollmer, AT Hattersley, BA Mateen, ... Diabetologia 64 (5), 1184-1186, 2021 | 28 | 2021 |
Sebastian J. VollmerUniversity of Kaiserslautern/DFKIVerified email at cs.uni-kl.de