@article{wornow2023ehrshot,title={Ehrshot: An ehr benchmark for few-shot evaluation of foundation models},author={Wornow*, Michael and Thapa*, Rahul and Steinberg, Ethan and Fries, Jason and Shah, Nigam},journal={arXiv preprint arXiv:2307.02028},year={2023},url={https://som-shahlab.github.io/ehrshot-website/},paper={https://arxiv.org/abs/2307.02028},dimensions={true},}
Springer
Machine Learning Differentiation of Autism Spectrum Sub-Classifications
R Thapa, A Garikipati, M Ciobanu, and 7 more authors
Journal of Autism and Developmental Disorders, 2023
@article{thapa2023machine,title={Machine Learning Differentiation of Autism Spectrum Sub-Classifications},author={Thapa, R and Garikipati, A and Ciobanu, M and Singh, NP and Browning, E and DeCurzio, J and Barnes, G and Dinenno, FA and Mao, Q and Das, R},journal={Journal of Autism and Developmental Disorders},pages={1--16},year={2023},publisher={Springer},}
Arxiv
Medalign: A clinician-generated dataset for instruction following with electronic medical records
Scott L Fleming, Alejandro Lozano, William J Haberkorn, and 8 more authors
@article{fleming2023medalign,title={Medalign: A clinician-generated dataset for instruction following with electronic medical records},author={Fleming, Scott L and Lozano, Alejandro and Haberkorn, William J and Jindal, Jenelle A and Reis, Eduardo P and Thapa, Rahul and Blankemeier, Louis and Genkins, Julian Z and Steinberg, Ethan and Nayak, Ashwin and others},journal={arXiv preprint arXiv:2308.14089},year={2023},}
Nature
The shaky foundations of large language models and foundation models for electronic health records
Michael Wornow, Yizhe Xu, Rahul Thapa, and 6 more authors
@article{wornow2023shaky,title={The shaky foundations of large language models and foundation models for electronic health records},author={Wornow, Michael and Xu, Yizhe and Thapa, Rahul and Patel, Birju and Steinberg, Ethan and Fleming, Scott and Pfeffer, Michael A and Fries, Jason and Shah, Nigam H},journal={npj Digital Medicine},volume={6},number={1},pages={135},year={2023},publisher={Nature Publishing Group UK London},}
Elsevier
Assessing the effects of data drift on the performance of machine learning models used in clinical sepsis prediction
Keyvan Rahmani*, Rahul Thapa*, Peiling Tsou, and 4 more authors
International Journal of Medical Informatics, 2023
@article{rahmani2023assessing,title={Assessing the effects of data drift on the performance of machine learning models used in clinical sepsis prediction},author={Rahmani*, Keyvan and Thapa*, Rahul and Tsou, Peiling and Chetty, Satish Casie and Barnes, Gina and Lam, Carson and Tso, Chak Foon},journal={International Journal of Medical Informatics},volume={173},pages={104930},year={2023},publisher={Elsevier},}
Arxiv
Evaluation of GPT-3.5 and GPT-4 for supporting real-world information needs in healthcare delivery
Debadutta Dash, Rahul Thapa, Juan M Banda, and 8 more authors
@article{dash2023evaluation,title={Evaluation of GPT-3.5 and GPT-4 for supporting real-world information needs in healthcare delivery},author={Dash, Debadutta and Thapa, Rahul and Banda, Juan M and Swaminathan, Akshay and Cheatham, Morgan and Kashyap, Mehr and Kotecha, Nikesh and Chen, Jonathan H and Gombar, Saurabh and Downing, Lance and others},journal={arXiv preprint arXiv:2304.13714},year={2023},}
2022
IEEE
MoleHD: Efficient Drug Discovery using Brain Inspired Hyperdimensional Computing
@inproceedings{ma2022molehd,title={MoleHD: Efficient Drug Discovery using Brain Inspired Hyperdimensional Computing},author={Ma, Dongning and Thapa, Rahul and Jiao, Xun},booktitle={2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)},pages={390--393},year={2022},organization={IEEE},}
JMIR
Multitask Learning With Recurrent Neural Networks for Acute Respiratory Distress Syndrome Prediction Using Only Electronic Health Record Data: Model Development and Validation Study
Carson Lam*, Rahul Thapa*, Jenish Maharjan, and 5 more authors
@article{lam2022multitask,title={Multitask Learning With Recurrent Neural Networks for Acute Respiratory Distress Syndrome Prediction Using Only Electronic Health Record Data: Model Development and Validation Study},author={Lam*, Carson and Thapa*, Rahul and Maharjan, Jenish and Rahmani, Keyvan and Tso, Chak Foon and Singh, Navan Preet and Casie Chetty, Satish and Mao, Qingqing},journal={JMIR Medical Informatics},volume={10},number={6},pages={e36202},year={2022},publisher={JMIR Publications Toronto, Canada},}
SSRN
A New Standard for Sepsis Prediction Algorithms: Using Time-Dependent Analysis for Earlier Clinically Relevant Alerts
Jenish Maharjan, Rahul Thapa, Jacob Calvert, and 8 more authors
@article{maharjan2022new,title={A New Standard for Sepsis Prediction Algorithms: Using Time-Dependent Analysis for Earlier Clinically Relevant Alerts},author={Maharjan, Jenish and Thapa, Rahul and Calvert, Jacob and Attwood, Misty M and Shokouhi, Sepideh and Casie Chetty, Satish and Iqbal, Zohora and Singh, Navan and Hoffman, Jana and Mataraso, Samson and others},journal={Available at SSRN 4130480},year={2022},}
JMIR
Predicting falls in long-term care facilities: machine learning study
Rahul Thapa, Anurag Garikipati, Sepideh Shokouhi, and 7 more authors
@article{thapa2022predicting,title={Predicting falls in long-term care facilities: machine learning study},author={Thapa, Rahul and Garikipati, Anurag and Shokouhi, Sepideh and Hurtado, Myrna and Barnes, Gina and Hoffman, Jana and Calvert, Jacob and Katzmann, Lynne and Mao, Qingqing and Das, Ritankar},journal={JMIR aging},volume={5},number={2},pages={e35373},year={2022},publisher={JMIR Publications Toronto, Canada},}
JGH
Machine learning to predict progression of non-alcoholic fatty liver to non-alcoholic steatohepatitis or fibrosis
Sina Ghandian*, Rahul Thapa*, Anurag Garikipati, and 5 more authors
@article{ghandian2022machine,title={Machine learning to predict progression of non-alcoholic fatty liver to non-alcoholic steatohepatitis or fibrosis},author={Ghandian*, Sina and Thapa*, Rahul and Garikipati, Anurag and Barnes, Gina and Green-Saxena, Abigail and Calvert, Jacob and Mao, Qingqing and Das, Ritankar},journal={JGH Open},volume={6},number={3},pages={196--204},year={2022},publisher={Wiley Online Library},}
Pancreatology
Early prediction of severe acute pancreatitis using machine learning
Rahul Thapa, Zohora Iqbal, Anurag Garikipati, and 4 more authors
@article{thapa2022early,title={Early prediction of severe acute pancreatitis using machine learning},author={Thapa, Rahul and Iqbal, Zohora and Garikipati, Anurag and Siefkas, Anna and Hoffman, Jana and Mao, Qingqing and Das, Ritankar},journal={Pancreatology},volume={22},number={1},pages={43--50},year={2022},publisher={Elsevier},}
2021
IEEE
Spamhd: Memory-efficient text spam detection using brain-inspired hyperdimensional computing
Rahul Thapa, Bikal Lamichhane, Dongning Ma, and 1 more author
In 2021 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 2021
@inproceedings{thapa2021spamhd,title={Spamhd: Memory-efficient text spam detection using brain-inspired hyperdimensional computing},author={Thapa, Rahul and Lamichhane, Bikal and Ma, Dongning and Jiao, Xun},booktitle={2021 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)},pages={84--89},year={2021},organization={IEEE},}
IEEE
Hdxplore: Automated blackbox testing of brain-inspired hyperdimensional computing
@inproceedings{thapa2021hdxplore,title={Hdxplore: Automated blackbox testing of brain-inspired hyperdimensional computing},author={Thapa, Rahul and Ma, Dongning and Jiao, Xun},booktitle={2021 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)},pages={90--95},year={2021},organization={IEEE},}
@inproceedings{ma2021workload,title={Workload-aware approximate computing configuration},author={Ma*, Dongning and Thapa*, Rahul and Wang, Xingjian and Jiao, Xun and Hao, Cong},booktitle={2021 Design, Automation \& Test in Europe Conference \& Exhibition (DATE)},pages={920--925},year={2021},organization={IEEE},}