| Fastshap: Real-time shapley value estimation N Jethani, M Sudarshan, IC Covert, SI Lee, R Ranganath International Conference on Learning Representations, 2021 | 82 | 2021 |
| Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations. N Jethani, M Sudarshan, Y Aphinyanaphongs, R Ranganath International Conference on Artificial Intelligence and Statistics, 1459-1467, 2021 | 49 | 2021 |
| Myocardial injury in adults hospitalized with COVID-19 NR Smilowitz, N Jethani, J Chen, Y Aphinyanaphongs, R Zhang, S Dogra, ... Circulation 142 (24), 2393-2395, 2020 | 40 | 2020 |
| Estimating real-world performance of a predictive model: a case-study in predicting mortality VJ Major, N Jethani, Y Aphinyanaphongs JAMIA open 3 (2), 243-251, 2020 | 12 | 2020 |
| Don’t be fooled: label leakage in explanation methods and the importance of their quantitative evaluation N Jethani, A Saporta, R Ranganath International Conference on Artificial Intelligence and Statistics, 8925-8953, 2023 | 3 | 2023 |
| Evaluating ChatGPT in Information Extraction: A Case Study of Extracting Cognitive Exam Dates and Scores N Jethani, S Jones, N Genes, VJ Major, IS Jaffe, AB Cardillo, ... | 1 | 2023 |
| New-Onset Diabetes Assessment Using Artificial Intelligence-Enhanced Electrocardiography N Jethani, A Puli, H Zhang, L Garber, L Jankelson, Y Aphinyanaphongs, ... arXiv preprint arXiv:2205.02900, 2022 | 1 | 2022 |
| QTNet: Predicting Drug-Induced QT Prolongation With Artificial Intelligence–Enabled Electrocardiograms H Zhang, C Tarabanis, N Jethani, M Goldstein, S Smith, L Chinitz, ... JACC: Clinical Electrophysiology, 2024 | | 2024 |
| Development and external validation of a dynamic risk score for early prediction of cardiogenic shock in cardiac intensive care units using machine learning Y Hu, A Lui, M Goldstein, M Sudarshan, A Tinsay, C Tsui, SD Maidman, ... European Heart Journal: Acute Cardiovascular Care, zuae037, 2024 | | 2024 |
| Deep Learning for the Prediction of Myocardial Scarring Through Electrocardiograms J Zhang, H Zhang, N Jethani, LA CHINITZ, Y Aphinyanaphongs, ... Circulation 148 (Suppl_1), A17893-A17893, 2023 | | 2023 |
| Evaluating Large Language Models in Extracting Cognitive Exam Dates and Scores H Zhang, N Jethani, S Jones, N Genes, VJ Major, IS Jaffe, AB Cardillo, ... medRxiv, 2023.07. 10.23292373, 2023 | | 2023 |
| PO-04-210 NEW-ONSET DIABETES SCREENING USING ARTIFICIAL INTELLIGENCE-ENHANCED ELECTROCARDIOGRAM L Jankelson, N Jethani, A Puli, H Zhang, L Garber, Y Aphinyanaphongs, ... Heart Rhythm 20 (5), S617-S618, 2023 | | 2023 |
| A dynamic risk score for early prediction of cardiogenic shock using machine learning Y Hu, A Lui, M Goldstein, M Sudarshan, A Tinsay, C Tsui, S Maidman, ... arXiv preprint arXiv:2303.12888, 2023 | | 2023 |
| Machine Learning for Knowledge Discovery: Modeling and Explaining High-Dimensional Healthcare Data N Jethani New York University, 2022 | | 2022 |
| B-PO05-162 DEVELOPMENT OF A QRS-AGNOSTIC QT CORRECTION METHOD USING DEEP LEARNING A Katz, X Han, N Jethani, C Barbhaiya, S Bernstein, D Holmes, R Knotts, ... Heart Rhythm 18 (8), S438, 2021 | | 2021 |
| B-PO03-175 QTNET: PREDICTING DRUG-INDUCED QT PROLONGATION WITH DEEP NEURAL NETWORKS N Jethani, H Zhang, LA Chinitz, Y Aphinyanaphongs, R Ranganath, ... Heart Rhythm 18 (8), S260-S261, 2021 | | 2021 |
| QTNet: Predicting Drug-Induced QT prolongation with Deep Neural Networks N Jethani, H Zhang, L Chinitz, Y Aphinyanaphongs, R Ranganath, ... medRxiv, 2021.03. 24.21254235, 2021 | | 2021 |
| Can We Learn to Explain Chest X-Rays?: A Cardiomegaly Use Case N Jethani, M Sudarshan, L Azour, W Moore, Y Aphinyanaphongs, ... | | |
