| Development and validation of machine learning models to identify high-risk surgical patients using automatically curated electronic health record data (Pythia): a … KM Corey, S Kashyap, E Lorenzi, SA Lagoo-Deenadayalan, K Heller, ... PLoS medicine 15 (11), e1002701, 2018 | 170 | 2018 |
| A path for translation of machine learning products into healthcare delivery MP Sendak, J D’Arcy, S Kashyap, M Gao, M Nichols, K Corey, W Ratliff, ... EMJ Innov 10, 19-00172, 2020 | 104 | 2020 |
| A framework for making predictive models useful in practice K Jung, S Kashyap, A Avati, S Harman, H Shaw, R Li, M Smith, K Shum, ... Journal of the American Medical Informatics Association 28 (6), 1149-1158, 2021 | 58 | 2021 |
| Measure what matters: counts of hospitalized patients are a better metric for health system capacity planning for a reopening S Kashyap, S Gombar, S Yadlowsky, A Callahan, J Fries, BA Pinsky, ... Journal of the American Medical Informatics Association 27 (7), 1026-1131, 2020 | 22 | 2020 |
| A survey of extant organizational and computational setups for deploying predictive models in health systems S Kashyap, KE Morse, B Patel, NH Shah Journal of the American Medical Informatics Association 28 (11), 2445-2450, 2021 | 19 | 2021 |
| Just-in-time postnatal education programmes to improve newborn care practices: needs and opportunities in low-resource settings L Subramanian, S Murthy, P Bogam, SD Yan, MM Delaney, ... BMJ global health 5 (7), e002660, 2020 | 14 | 2020 |
| Machine Learning for Health (ML4H) 2019: What Makes Machine Learning in Medicine Different? AV Dalca, MBA McDermott, E Alsentzer, SG Finlayson, M Oberst, F Falck, ... Machine Learning for Health Workshop, 1-9, 2020 | 4 | 2020 |
| Impact of family-centred postnatal training on maternal and neonatal health and care practices in district hospitals in two states in India: a pre–post study S Kashyap, AF Spielman, N Ramnarayan, SD Sahana, R Pant, B Kaur, ... BMJ Open Quality 11 (Suppl 1), e001462, 2022 | 3 | 2022 |
| Impact of diagnosis code grouping method on clinical prediction model performance: a multi-site retrospective observational study A Kansal, M Gao, S Balu, M Nichols, K Corey, S Kashyap, M Sendak International Journal of Medical Informatics 151, 104466, 2021 | 3 | 2021 |
| Machine learning for predictive analytics S Kashyap, KM Corey, A Kansal, M Sendak Machine Learning in Cardiovascular Medicine, 45-69, 2021 | 1 | 2021 |
| Family-centered postnatal training and adherence to newborn care practices in district hospitals in two Indian states: A quasi-experimental intervention study S Kashyap, AF Spielman, N Ramnarayan, SD Sahana, R Pant, B Kaur, ... medRxiv, 2021.03. 15.21252605, 2021 | | 2021 |
| Early Identification of High Risk Cardiac Decompensation Phenotypes via Real-time Electronic Health Record Data W Ratliff, ZK Wegermann, H Shi, M Gao, M Sendak, A Kansal, C O'Brien, ... Circulation 142 (Suppl_3), A16450-A16450, 2020 | | 2020 |
| Does Explant Histology Predict HCV Recurrence? R Kashyap, S Kahyap, S Safadjou, C Ryan, N Yarid, S Agarwal, ... AMERICAN JOURNAL OF TRANSPLANTATION 10, 258-258, 2010 | | 2010 |
| The Limits of Removing Uncertainty: The Role of Computational Science in Scientific Inquiry S Metz | | |
Mark SendakPopulation Health & Data Science Lead, Duke Institute for Health InnovationVerified email at duke.edu
