| Characterizing treatment pathways at scale using the OHDSI network G Hripcsak, PB Ryan, JD Duke, NH Shah, RW Park, V Huser, MA Suchard, ... Proceedings of the National Academy of Sciences 113 (27), 7329-7336, 2016 | 369 | 2016 |
| Diagnosis code assignment: models and evaluation metrics A Perotte, R Pivovarov, K Natarajan, N Weiskopf, F Wood, N Elhadad Journal of the American Medical Informatics Association 21 (2), 231-237, 2014 | 289 | 2014 |
| Deep survival analysis R Ranganath, A Perotte, N Elhadad, D Blei Machine Learning for Healthcare Conference, 101-114, 2016 | 258 | 2016 |
| Nonconvulsive seizures after subarachnoid hemorrhage: multimodal detection and outcomes J Claassen, A Perotte, D Albers, S Kleinberg, JM Schmidt, B Tu, ... Annals of neurology 74 (1), 53-64, 2013 | 218 | 2013 |
| Challenges with quality of race and ethnicity data in observational databases FCG Polubriaginof, P Ryan, H Salmasian, AW Shapiro, A Perotte, ... Journal of the American Medical Informatics Association 26 (8-9), 730-736, 2019 | 183 | 2019 |
| Hierarchically supervised latent Dirichlet allocation A Perotte, F Wood, N Elhadad, N Bartlett Advances in neural information processing systems 24, 2011 | 182 | 2011 |
| Learning probabilistic phenotypes from heterogeneous EHR data R Pivovarov, AJ Perotte, E Grave, J Angiolillo, CH Wiggins, N Elhadad Journal of biomedical informatics 58, 156-165, 2015 | 167 | 2015 |
| Risk prediction for chronic kidney disease progression using heterogeneous electronic health record data and time series analysis A Perotte, R Ranganath, JS Hirsch, D Blei, N Elhadad Journal of the American Medical Informatics Association 22 (4), 872-880, 2015 | 134 | 2015 |
| Methods for reducing interference in the complementary learning systems model: oscillating inhibition and autonomous memory rehearsal KA Norman, EL Newman, AJ Perotte Neural Networks 18 (9), 1212-1228, 2005 | 122 | 2005 |
| Translating evidence into practice: eligibility criteria fail to eliminate clinically significant differences between real-world and study populations AJ Averitt, C Weng, P Ryan, A Perotte NPJ digital medicine 3 (1), 67, 2020 | 119 | 2020 |
| Deep learning electrocardiographic analysis for detection of left-sided valvular heart disease P Elias, TJ Poterucha, V Rajaram, LM Moller, V Rodriguez, S Bhave, ... Journal of the American College of Cardiology 80 (6), 613-626, 2022 | 101 | 2022 |
| Elevated GM3 plasma concentration in idiopathic Parkinson’s disease: A lipidomic analysis RB Chan, AJ Perotte, B Zhou, C Liong, EJ Shorr, KS Marder, UJ Kang, ... PloS one 12 (2), e0172348, 2017 | 99 | 2017 |
| Parameterizing time in electronic health record studies G Hripcsak, DJ Albers, A Perotte Journal of the American Medical Informatics Association 22 (4), 794-804, 2015 | 94 | 2015 |
| Diagnosing transthyretin cardiac amyloidosis by technetium Tc 99m pyrophosphate: a test in evolution TJ Poterucha, P Elias, S Bokhari, AJ Einstein, A DeLuca, M Kinkhabwala, ... Cardiovascular Imaging 14 (6), 1221-1231, 2021 | 91 | 2021 |
| Trends in poor health indicators among Black and Hispanic middle-aged and older adults in the United States, 1999-2018 M Odlum, N Moise, IM Kronish, P Broadwell, C Alcántara, NJ Davis, ... JAMA Network Open 3 (11), e2025134-e2025134, 2020 | 86 | 2020 |
| High rate of renal recovery in survivors of COVID-19 associated acute renal failure requiring renal replacement therapy JS Stevens, KL King, SY Robbins-Juarez, P Khairallah, K Toma, ... PLoS One 15 (12), e0244131, 2020 | 79 | 2020 |
| A collaborative approach to developing an electronic health record phenotyping algorithm for drug-induced liver injury CL Overby, J Pathak, O Gottesman, K Haerian, A Perotte, S Murphy, ... Journal of the American Medical Informatics Association 20 (e2), e243-e252, 2013 | 79 | 2013 |
| Exploiting time in electronic health record correlations G Hripcsak, DJ Albers, A Perotte Journal of the American Medical Informatics Association 18 (Suppl 1), i109-i115, 2011 | 79 | 2011 |
| Detecting social and behavioral determinants of health with structured and free-text clinical data DJ Feller, OJB Don't Walk, J Zucker, MT Yin, P Gordon, N Elhadad Applied clinical informatics 11 (01), 172-181, 2020 | 66 | 2020 |
| CEHR-BERT: Incorporating temporal information from structured EHR data to improve prediction tasks C Pang, X Jiang, KS Kalluri, M Spotnitz, RJ Chen, A Perotte, K Natarajan Machine Learning for Health, 239-260, 2021 | 64 | 2021 |
Noémie ElhadadAssociate Professor and Chair of Biomedical Informatics, Columbia UniversityVerifisert e-postadresse på cumc.columbia.edu
