| The “inconvenient truth” about AI in healthcare T Panch, H Mattie, LA Celi Npj Digital Medicine 2 (1), 1-3, 2019 | 436 | 2019 |
| Artificial intelligence and algorithmic bias: implications for health systems T Panch, H Mattie, R Atun Journal of Global Health 9 (2), 2019 | 428 | 2019 |
| Performance of intensive care unit severity scoring systems across different ethnicities in the USA: a retrospective observational study R Sarkar, C Martin, H Mattie, JW Gichoya, DJ Stone, LA Celi The Lancet Digital Health 3 (4), e241-e249, 2021 | 63 | 2021 |
| Best practices in the real-world data life cycle J Zhang, J Symons, P Agapow, JT Teo, CA Paxton, J Abdi, H Mattie, ... PLOS Digital Health 1 (1), e0000003, 2022 | 55 | 2022 |
| Understanding tie strength in social networks using a local “bow tie” framework H Mattie, K Engø-Monsen, R Ling, JP Onnela Scientific reports 8 (1), 9349, 2018 | 55 | 2018 |
| Dating app use and unhealthy weight control behaviors among a sample of US adults: a cross-sectional study A Tran, C Suharlim, H Mattie, K Davison, M Agénor, SB Austin Journal of Eating Disorders 7 (1), 16, 2019 | 51 | 2019 |
| An interactive dashboard to track themes, development maturity, and global equity in clinical artificial intelligence research J Zhang, S Whebell, J Gallifant, S Budhdeo, H Mattie, ... The Lancet Digital Health 4 (4), e212-e213, 2022 | 49 | 2022 |
| A distributed approach to the regulation of clinical AI T Panch, E Duralde, H Mattie, G Kotecha, LA Celi, M Wright, F Greaves PLOS Digital Health 1 (5), e0000040, 2022 | 22 | 2022 |
| Turning the crank for machine learning: ease, at what expense? TJ Pollard, I Chen, J Wiens, S Horng, D Wong, M Ghassemi, H Mattie, ... The Lancet Digital Health 1 (5), e198-e199, 2019 | 20 | 2019 |
| “Yes, but will it work for my patients?” Driving clinically relevant research with benchmark datasets T Panch, TJ Pollard, H Mattie, E Lindemer, PA Keane, LA Celi NPJ digital medicine 3 (1), 87, 2020 | 19 | 2020 |
| The “inconvenient truth” about AI in healthcare. Npj Digital Medicine 2 (1), 77 T Panch, H Mattie, LA Celi Aug, 2019 | 19 | 2019 |
| Machine Learning for Acute Kidney Injury Prediction in the Intensive Care Unit ER Gottlieb, M Samuel, JV Bonventre, LA Celi, H Mattie Advances in Chronic Kidney Disease 29 (5), 431-438, 2022 | 18 | 2022 |
| Data science in public health: building next generation capacity N Mirin, H Mattie, L Jackson, Z Samad, R Chunara arXiv preprint arXiv:2208.03461, 2022 | 7 | 2022 |
| A framework for predicting impactability of digital care management using machine learning methods H Mattie, P Reidy, P Bachtiger, E Lindemer, N Nikolaev, M Jouni, ... Population health management 23 (4), 319-325, 2020 | 7 | 2020 |
| The “inconvenient truth” about AI in healthcare. npj Digit. Med. 2, 77 (2019) T Panch, H Mattie, LA Celi | 7 | |
| Addressing the “elephant in the room” of AI clinical decision support through organisation-level regulation J Zhang, H Mattie, H Shuaib, T Hensman, JT Teo, LA Celi PLOS Digital Health 1 (9), e0000111, 2022 | 6 | 2022 |
| Traditional Machine Learning Methods versus Deep Learning for Meningioma Classification, Grading, Outcome Prediction, and Segmentation: A Systematic Review and Meta-Analysis KM Maniar, P Lassarén, A Rana, Y Yao, IA Tewarie, JVE Gerstl, ... World neurosurgery 179, e119-e134, 2023 | 5 | 2023 |
| Traditional Machine Learning Methods versus Deep Learning for Meningioma Classification, Grading, Outcome Prediction, and Segmentation: A Systematic Review and Meta-Analysis KM Maniar, P Lassarén, A Rana, Y Yao, IA Tewarie, JVE Gerstl, ... World Neurosurgery, 2023 | 5 | 2023 |
| Edge overlap in weighted and directed social networks H Mattie, JP Onnela Network Science 9 (2), 179-193, 2021 | 5 | 2021 |
| Generalizations of Edge Overlap to Weighted and Directed Networks H Mattie, JP Onnela arXiv preprint arXiv:1712.07110, 2017 | 5 | 2017 |
Leo Anthony CeliMassachusetts Institute of TechnologyE-mail megerősítve itt: mit.edu