| The shaky foundations of large language models and foundation models for electronic health records M Wornow, Y Xu, R Thapa, B Patel, E Steinberg, S Fleming, MA Pfeffer, ... npj digital medicine 6 (1), 135, 2023 | 278 | 2023 |
| Medalign: A clinician-generated dataset for instruction following with electronic medical records SL Fleming, A Lozano, WJ Haberkorn, JA Jindal, E Reis, R Thapa, ... Proceedings of the AAAI Conference on Artificial Intelligence 38 (20), 22021 …, 2024 | 109 | 2024 |
| Ehrshot: An ehr benchmark for few-shot evaluation of foundation models M Wornow, R Thapa, E Steinberg, J Fries, N Shah Advances in Neural Information Processing Systems 36, 67125-67137, 2023 | 96 | 2023 |
| Assessing the effects of data drift on the performance of machine learning models used in clinical sepsis prediction K Rahmani, R Thapa, P Tsou, SC Chetty, G Barnes, C Lam, CF Tso International Journal of Medical Informatics 173, 104930, 2023 | 95 | 2023 |
| OpenMedLM: prompt engineering can out-perform fine-tuning in medical question-answering with open-source large language models J Maharjan, A Garikipati, NP Singh, L Cyrus, M Sharma, M Ciobanu, ... Scientific Reports 14 (1), 14156, 2024 | 81 | 2024 |
| DEPLOYR: a technical framework for deploying custom real-time machine learning models into the electronic medical record CK Corbin, R Maclay, A Acharya, S Mony, S Punnathanam, R Thapa, ... Journal of the American Medical Informatics Association 30 (9), 1532-1542, 2023 | 78 | 2023 |
| Evaluation of GPT-3.5 and GPT-4 for supporting real-world information needs in healthcare delivery D Dash, R Thapa, JM Banda, A Swaminathan, M Cheatham, M Kashyap, ... arXiv preprint arXiv:2304.13714, 2023 | 76 | 2023 |
| Early prediction of severe acute pancreatitis using machine learning R Thapa, Z Iqbal, A Garikipati, A Siefkas, J Hoffman, Q Mao, R Das Pancreatology 22 (1), 43-50, 2022 | 58 | 2022 |
| Octotools: An agentic framework with extensible tools for complex reasoning P Lu, B Chen, S Liu, R Thapa, J Boen, J Zou arXiv preprint arXiv:2502.11271, 2025 | 56 | 2025 |
| Standing on FURM ground: a framework for evaluating fair, useful, and reliable AI models in health care systems A Callahan, D McElfresh, JM Banda, G Bunney, D Char, J Chen, ... NEJM Catalyst Innovations in Care Delivery 5 (10), CAT. 24.0131, 2024 | 45 | 2024 |
| The shaky foundations of clinical foundation models: A survey of large language models and foundation models for emrs M Wornow, Y Xu, R Thapa, B Patel, E Steinberg, S Fleming, MA Pfeffer, ... arXiv preprint arXiv:2303.12961, 2023 | 45* | 2023 |
| SleepFM: Multi-modal representation learning for sleep across brain activity, ECG and respiratory signals R Thapa, B He, MR Kjaer, H Moore, G Ganjoo, E Mignot, J Zou arXiv preprint arXiv:2405.17766, 2024 | 42 | 2024 |
| Predicting falls in long-term care facilities: machine learning study R Thapa, A Garikipati, S Shokouhi, M Hurtado, G Barnes, J Hoffman, ... JMIR aging 5 (2), e35373, 2022 | 42 | 2022 |
| Spamhd: Memory-efficient text spam detection using brain-inspired hyperdimensional computing R Thapa, B Lamichhane, D Ma, X Jiao 2021 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 84-89, 2021 | 33 | 2021 |
| Machine learning differentiation of autism spectrum sub-classifications R Thapa, A Garikipati, M Ciobanu, NP Singh, E Browning, J DeCurzio, ... Journal of Autism and Developmental Disorders 54 (11), 4216-4231, 2024 | 30 | 2024 |
| Machine learning to predict progression of non‐alcoholic fatty liver to non‐alcoholic steatohepatitis or fibrosis S Ghandian, R Thapa, A Garikipati, G Barnes, A Green‐Saxena, J Calvert, ... JGH Open 6 (3), 196-204, 2022 | 27 | 2022 |
| Multitask learning with recurrent neural networks for acute respiratory distress syndrome prediction using only electronic health record data: model development and validation … C Lam, R Thapa, J Maharjan, K Rahmani, CF Tso, NP Singh, ... JMIR Medical Informatics 10 (6), e36202, 2022 | 23 | 2022 |
| Sleepfm: Multi-modal representation learning for sleep across ecg, eeg and respiratory signals R Thapa, B He, MR Kjaer, H Moore IV, G Ganjoo, E Mignot, JY Zou AAAI 2024 Spring Symposium on Clinical Foundation Models, 2024 | 21 | 2024 |
| Workload-aware approximate computing configuration D Ma, R Thapa, X Wang, X Jiao, C Hao 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE), 920-925, 2021 | 20 | 2021 |
| Hdxplore: Automated blackbox testing of brain-inspired hyperdimensional computing R Thapa, D Ma, X Jiao 2021 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 90-95, 2021 | 17 | 2021 |
James ZouStanford UniversityVerified email at stanford.edu
