Investigating Poor Performance Regions of Black Boxes: LIME-based Exploration in Sepsis Detection. - Mozhgan Salimiparsa; Surajsinh Parmar; San Lee; Choongmin Kim; Yonghwan Kim; Jang Yong Kim (xAI (Late-breaking Work, Demos, Doctoral Consortium), 2023)

Extending Machine Learning-Based Early Sepsis Detection to Different Demographics. - Surajsinh Parmar; Tao Shan; San Lee; Yonghwan Kim; Jang Yong Kim (CoRR, 2023)

SM70: A Large Language Model for Medical Devices. - Anubhav Bhatti; Surajsinh Parmar; San Lee (CoRR, 2023)

Low-Rank Adaptation of Time Series Foundational Models for Out-of-Domain Modality Forecasting. - Divij Gupta; Anubhav Bhatti; Suraj Parmar; Chen Dan 005; Yuwei Liu; Bingjie Shen; San Lee (ICMI, 2024)

Interpretable Vital Sign Forecasting with Model Agnostic Attention Maps. - Yuwei Liu; Chen Dan 005; Anubhav Bhatti; Bingjie Shen; Divij Gupta; Suraj Parmar; San Lee (xAI (Late-breaking Work, Demos, Doctoral Consortium), 2024)

Towards Democratizing Multilingual Large Language Models For Medicine Through A Two-Stage Instruction Fine-tuning Approach. - Meng Zhou; Surajsinh Parmar; Anubhav Bhatti (CoRR, 2024)

Beyond LoRA: Exploring Efficient Fine-Tuning Techniques for Time Series Foundational Models. - Divij Gupta; Anubhav Bhatti; Surajsinh Parmar (CoRR, 2024)