| Artificial intelligence, machine learning and health systems T Panch, P Szolovits, R Atun Journal of global health 8 (2), 2018 | 659 | 2018 |
| The “inconvenient truth” about AI in healthcare T Panch, H Mattie, LA Celi NPJ digital medicine 2 (1), 1-3, 2019 | 426 | 2019 |
| Artificial intelligence and algorithmic bias: implications for health systems T Panch, H Mattie, R Atun Journal of global health 9 (2), 2019 | 422 | 2019 |
| The myth of generalisability in clinical research and machine learning in health care J Futoma, M Simons, T Panch, F Doshi-Velez, LA Celi The Lancet Digital Health 2 (9), e489-e492, 2020 | 355 | 2020 |
| Developing specific reporting guidelines for diagnostic accuracy studies assessing AI interventions: The STARD-AI Steering Group V Sounderajah, H Ashrafian, R Aggarwal, J De Fauw, AK Denniston, ... Nature medicine 26 (6), 807-808, 2020 | 227 | 2020 |
| 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 |
| Artificial intelligence: opportunities and risks for public health T Panch, J Pearson-Stuttard, F Greaves, R Atun The Lancet Digital Health 1 (1), e13-e14, 2019 | 152 | 2019 |
| Are single-item global ratings useful for assessing health status? C Macias, PB Gold, D Öngür, BM Cohen, T Panch Journal of clinical psychology in medical settings 22, 251-264, 2015 | 114 | 2015 |
| Utility and efficacy of a smartphone application to enhance the learning and behavior goals of traditional cardiac rehabilitation: a feasibility study DE Forman, K LaFond, T Panch, K Allsup, K Manning, J Sattelmair Journal of cardiopulmonary rehabilitation and prevention 34 (5), 327-334, 2014 | 105 | 2014 |
| Using smartphone apps to promote psychiatric and physical well-being C Macias, T Panch, YM Hicks, JS Scolnick, DL Weene, D Öngür, ... Psychiatric Quarterly 86, 505-519, 2015 | 92 | 2015 |
| The role of artificial intelligence in orthopaedic surgery JR Panchmatia, MR Visenio, T Panch British Journal of Hospital Medicine 79 (12), 676-681, 2018 | 46 | 2018 |
| Hallucination or confabulation? neuroanatomy as metaphor in large language models AL Smith, F Greaves, T Panch PLOS Digital Health 2 (11), e0000388, 2023 | 35 | 2023 |
| The role of mobile health in elderly populations BJ Gilbert, E Goodman, A Chadda, D Hatfield, DE Forman, T Panch Current Geriatrics Reports 4, 347-352, 2015 | 33 | 2015 |
| Using smartphone apps to promote psychiatric rehabilitation in a peer-led community support program: pilot study NE Mueller, T Panch, C Macias, BM Cohen, D Ongur, JT Baker JMIR mental health 5 (3), e10092, 2018 | 30 | 2018 |
| 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 |
| “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 |
| 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 | 19 | 2019 |
| From volume to value? can a value-based approach help deliver the ambitious aims of the NHS cardiovascular disease outcomes strategy? R Dunbar-Rees, T Panch, M Dancy Heart 100 (11), 827-832, 2014 | 13 | 2014 |
| Apparatus and method for improving compliance with a therapeutic regimen T Panch, V Ramesh, A Bhise, J Sattelmair US Patent 9,805,163, 2017 | 11 | 2017 |
| Machine learning health-related applications in low-income and middle-income countries: a scoping review protocol RM Carrillo-Larco, LT Car, J Pearson-Stuttard, T Panch, JJ Miranda, ... BMJ open 10 (5), e035983, 2020 | 8 | 2020 |
Heather MattieHarvard T.H. Chan School of Public Health在 g.harvard.edu 的电子邮件经过验证