3 citations · 7 across the 7 of their papers we have counts for
5 papers · 1 filter
Patients With Personality: Realistic Patient Simulation through Controlled Diversity and Selective Disclosure
Moritz Schlager, Friederike Jungmann, Samuel Schmidgall +12
Simulating realistic patient interactions is a key requirement to testing clinical applications of LLMs at scale without time-consuming and expensive user studies. However, existin…
A prospective clinical feasibility study of a conversational diagnostic AI in an ambulatory primary care clinic
Peter Brodeur, Jacob M. Koshy, Anil Palepu +45
Large language model (LLM)-based AI systems have shown promise for patient-facing diagnostic and management conversations in simulated settings. Translating these systems into clin…
Towards Better Health Conversations: The Benefits of Context-seeking
Rory Sayres, Yuexing Hao, Abbi Ward +21
Navigating health questions can be daunting in the modern information landscape. Large language models (LLMs) may provide tailored, accessible information, but also risk being inac…
Exploring Large Language Models for Specialist-level Oncology Care
Anil Palepu, Vikram Dhillon, Polly Niravath +18
Large language models (LLMs) have shown remarkable progress in encoding clinical knowledge and responding to complex medical queries with appropriate clinical reasoning. However, t…
Towards Democratization of Subspeciality Medical Expertise
Jack W. O'Sullivan, Anil Palepu, Khaled Saab +23
The scarcity of subspecialist medical expertise, particularly in rare, complex and life-threatening diseases, poses a significant challenge for healthcare delivery. This issue is p…