Researcher
Clinically Relevant AI for Radiology, Oncology, and Global Health
Overview
Bridging radiology, clinical AI, and global health informatics through collaborative research.
Satvik Tripathi is a researcher at the Perelman School of Medicine at the University of Pennsylvania, working across Radiology and Radiation Oncology with a focus on clinically relevant AI for radiology, oncology, and patient-centered care.
He is an Innovation Fellow at the Penn Center for Cancer Care Innovation (PC3I) within the Abramson Cancer Center, advancing cancer care delivery through health system innovation and AI to improve quality, equity, and patient-centered outcomes.
In parallel, he is a research assistant at the Athinoula A. Martinos Center for Biomedical Imaging and in the Division of Vascular & Interventional Radiology at Mass General Hospital / Harvard Medical School, contributing to imaging AI methods and clinical applications in vascular radiology.
He also serves as an AI Scientist with RAD-AID International and is on the RSNA Radiology: Artificial Intelligence Trainee Editorial Board, with additional editorial leadership in the Radiology AI Podcast.
He holds leadership roles within SIIM, including Jr. Vice Chair (Membership Committee), and serves on SIIM’s Global Outreach and Machine Learning Education committees.
Profile Snapshot
Current collaborations, leadership roles, and research activity.
3+
Active academic hubs (Penn Medicine, MGH/HMS, Martinos Center)
6
Core themes across radiology AI, oncology, LLMs, and global health
4+
Leadership and service roles (RAD-AID, RSNA, SIIM)
Collaborations
Research groups and clinical partners supporting imaging AI work.
Work spanning clinical workflow AI, scalable infrastructure in low-resource settings, and cancer care innovation.
Imaging AI research and interventional radiology clinical applications.
Expertise
Key topics guiding current research and innovation priorities.
Initiatives
Active project streams and research focus areas.
Deployment-oriented AI tools for imaging workflows, focusing on real-world evaluation, safety, and clinician feedback.
AI-enabled health system innovation for quality, equity, and patient-centered outcomes through Penn Medicine partnerships.
Scalable AI infrastructure and deployment in low- and middle-income settings through global partnerships and RAD-AID outreach.
Updates
Recent awards, roles, and milestones.
Appointed Associate Editor, Radiology AI Podcast.
Selected for the RSNA Radiology: Artificial Intelligence Trainee Editorial Board.
Began Innovation Fellowship at the Penn Center for Cancer Care Innovation (PC3I).
Joined RAD-AID International as an AI Scientist.
Publications
Recent work spanning radiology AI, LLMs, and clinical translation.
NEJM AI NEJM AI, 2025
Introduced standardized reporting checklist for LLM-based radiology research.
JACR Journal of the American College of Radiology, 2025
Framework for reliable prompting in clinical radiology applications.
EJR European Journal of Radiology, 2025
Structured LLM reporting improving clinical readability and reliability.
JACR Journal of the American College of Radiology, 2025
Generative AI methods to improve pediatric patient education accessibility.
Radiology Radiology, 2025
Demonstrated viability of open-source LLMs for clinical radiology tasks.
Academic Radiology Academic Radiology, 2024
Governance and implementation considerations for clinical LLM deployment.
Current Problems in Diagnostic Radiology Current Problems in Diagnostic Radiology, 2024
JACR Journal of the American College of Radiology, 2023
Informatics in Medicine Unlocked Informatics in Medicine Unlocked, 2022
Leadership
Editorial leadership, global health service, and professional contributions in radiology AI.