Sam Rawal, MD, MS
I’m an Internal Medicine resident at Mayo Clinic and computer scientist working in clinical AI.
I work on developing tools to augment clinicians in order to better understand complex medical information, reason through patient-specific decisions, and advance medical care.
Selected Work A few highlights; see the navigation for more.
Software
Through my experiences as a resident physician, I have been focusing on developing tools that use AI to augment clinician reasoning, rather than replace it. These projects reflect some thoughts on how clinical AI can be useful from a practical, physician-first standpoint.
Osler
Tools for clinical reasoning. A workspace and copilot for physicians to augment the process of developing clinical plans, tracking ongoing care, and improve notes.
Pearls
An app for capturing clinical pearls on rounds or while studying. A built-in AI agent can add context, current guidelines, and useful tags to the original observation.
Research
I have been involved in clinical Natural Language Processing research since 2015. I'm currently a member of the Mayo AI in Medicine Program in the BEACON Lab. Previously, I was in the Cognition and Intelligence Lab at ASU. Below are a few highlights.
MIRIAD: Augmenting LLMs with millions of medical query-response pairs
A curated corpus of approximately 5.8 million medical question–answer pairs grounded in peer-reviewed literature, built to improve retrieval and reduce hallucinations in medical question answering.
Read the paper
SCORE-IT: A Machine Learning-based Tool for Automatic Standardization of EEG Reports
A machine-learning system for automatically standardizing clinical EEG reports.
🏆 Best Paper · IEEE SPMB 2021
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🏆 $100K grant
OSLER: An AI-Powered Clinical Reasoning Workspace for Graduate Medical Education
Awarded through the 2026 Mayo Clinic–Arizona State University Alliance for Health Care.
Multi-Perspective Biomedical Semantic Question-Answering
A semantic retrieval system that combines multiple Transformer and information-retrieval perspectives to find answers across biomedical literature.
