Rahul Thapa

According to our database, Rahul Thapa authored at least 16 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Dragonfly: Multi-Resolution Zoom Supercharges Large Visual-Language Model.

Kezhen Chen, Rahul Thapa, Rahul Chalamala, Ben Athiwaratkun, Shuaiwen Leon Song, James Zou

CoRR, 2024

Standing on FURM ground - A framework for evaluating Fair, Useful, and Reliable AI Models in healthcare systems.

Alison Callahan, Duncan C. McElfresh, Juan M. Banda, Gabrielle Bunney, Danton Char, Jonathan H. Chen, Conor K. Corbin, Debadutta Dash, Norman L. Downing, Sneha S. Jain, Nikesh Kotecha, Jonathan Masterson, Michelle M. Mello, Keith E. Morse, Srikar Nallan, Abby Pandya, Anurang Revri, Aditya Sharma, Christopher D. Sharp, Rahul Thapa, Michael Wornow, Alaa Youssef, Michael A. Pfeffer, Nigam H. Shah

CoRR, 2024

Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium.

Hyewon Jeong, Sarah Jabbour, Yuzhe Yang, Rahul Thapa, Hussein Mozannar, William Jongwon Han, Nikita Mehandru, Michael Wornow, Vladislav Lialin, Xin Liu, Alejandro Lozano, Jiacheng Zhu, Rafal Dariusz Kocielnik, Keith Harrigian, Haoran Zhang, Edward Lee, Milos Vukadinovic, Aparna Balagopalan, Vincent Jeanselme, Katherine Matton, Ilker Demirel, Jason A. Fries, Parisa Rashidi, Brett K. Beaulieu-Jones, Xuhai Orson Xu, Matthew B. A. McDermott, Tristan Naumann, Monica Agrawal, Marinka Zitnik, Berk Ustun, Edward Choi, Kristen Yeom, Gamze Gürsoy, Marzyeh Ghassemi, Emma Pierson, George H. Chen, Sanjat Kanjilal, Michael Oberst, Linying Zhang, Harvineet Singh, Tom Hartvigsen, Helen Zhou, Chinasa T. Okolo

CoRR, 2024

OpenMedLM: Prompt engineering can out-perform fine-tuning in medical question-answering with open-source large language models.

Jenish Maharjan, Anurag Garikipati, Navan Preet Singh, Leo Cyrus, Mayank Sharma, Madalina G. Ciobanu, Gina Barnes, Rahul Thapa, Qingqing Mao, Ritankar Das

CoRR, 2024

SleepFM: Multi-modal Representation Learning for Sleep Across Brain Activity, ECG and Respiratory Signals.

Rahul Thapa, Bryan He, Magnus Ruud Kjær, Hyatt E. Moore IV, Gauri Ganjoo, Emmanuel Mignot, James Zou

Proceedings of the Forty-first International Conference on Machine Learning, 2024

MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records.

Scott L. Fleming, Alejandro Lozano, William J. Haberkorn, Jenelle A. Jindal, Eduardo Pontes Reis, Rahul Thapa, Louis Blankemeier, Julian Z. Genkins, Ethan Steinberg, Ashwin Nayak, Birju S. Patel, Chia-Chun Chiang, Alison Callahan, Zepeng Huo, Sergios Gatidis, Scott J. Adams, Oluseyi Fayanju, Shreya J. Shah, Thomas Savage, Ethan Goh, Akshay S. Chaudhari, Nima Aghaeepour, Christopher D. Sharp, Michael A. Pfeffer, Percy Liang, Jonathan H. Chen, Keith E. Morse, Emma P. Brunskill, Jason A. Fries, Nigam H. Shah

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

DEPLOYR: a technical framework for deploying custom real-time machine learning models into the electronic medical record.

Conor K. Corbin, Rob Maclay, Aakash Acharya, Sreedevi Mony, Soumya Punnathanam, Rahul Thapa, Nikesh Kotecha, Nigam H. Shah, Jonathan H. Chen

J. Am. Medical Informatics Assoc., August, 2023

Assessing the effects of data drift on the performance of machine learning models used in clinical sepsis prediction.

Keyvan Rahmani, Rahul Thapa, Pei-Ling Tsou, Satish Casie Chetty, Gina Barnes, Carson K. Lam, Chak Foon Tso

Int. J. Medical Informatics, May, 2023

The shaky foundations of large language models and foundation models for electronic health records.

Michael Wornow, Yizhe Xu, Rahul Thapa, Birju S. Patel, Ethan Steinberg, Scott L. Fleming, Michael A. Pfeffer, Jason Alan Fries, Nigam H. Shah

npj Digit. Medicine, 2023

Evaluation of GPT-3.5 and GPT-4 for supporting real-world information needs in healthcare delivery.

Debadutta Dash, Rahul Thapa, Juan M. Banda, Akshay Swaminathan, Morgan Cheatham, Mehr Kashyap, Nikesh Kotecha, Jonathan H. Chen, Saurabh Gombar, Lance Downing, Rachel Pedreira, Ethan Goh, Angel Arnaout, Garret Kenn Morris, Honor Magon, Matthew P. Lungren, Eric Horvitz, Nigam H. Shah

CoRR, 2023

The Shaky Foundations of Clinical Foundation Models: A Survey of Large Language Models and Foundation Models for EMRs.

Michael Wornow, Yizhe Xu, Rahul Thapa, Birju S. Patel, Ethan Steinberg, Scott L. Fleming, Michael A. Pfeffer, Jason A. Fries, Nigam H. Shah

CoRR, 2023

EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models.

Michael Wornow, Rahul Thapa, Ethan Steinberg, Jason A. Fries, Nigam Shah

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

MoleHD: Efficient Drug Discovery using Brain Inspired Hyperdimensional Computing.

Dongning Ma, Rahul Thapa, Xun Jiao

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

2021

HDXplore: Automated Blackbox Testing of Brain-Inspired Hyperdimensional Computing.

Rahul Thapa, Dongning Ma, Xun Jiao

Proceedings of the IEEE Computer Society Annual Symposium on VLSI, 2021

SpamHD: Memory-Efficient Text Spam Detection using Brain-Inspired Hyperdimensional Computing.

Rahul Thapa, Bikal Lamichhane, Dongning Ma, Xun Jiao

Proceedings of the IEEE Computer Society Annual Symposium on VLSI, 2021

Workload-Aware Approximate Computing Configuration.

Dongning Ma, Rahul Thapa, Xingjian Wang, Xun Jiao, Cong Hao

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021