activity
20232026
most citedTowards Conversational Diagnostic AI

100 citations · 440 across the 13 of their papers we have counts for

collaborators

15 papers

cs.AI2026

Towards Expert-level Medical AI for Real-time Video Consultations

Mahvish Nagda, Jihyeon Lee, Matthew Thompson +37

Audio-visual interaction is the standard for patient-physician consultations, enabling natural communication and effective assessment of illness through non-verbal cues. While text…

cs.AI2026

ResidencyRL: Reinforcement Learning in Simulated Clinical Environments

Valentin Liévin, Samuel Schmidgall, Tim Strother +32

In medical education, physicians convert academic knowledge into clinical expertise through residency: years of training across thousands of encounters, with diverse sources of fee…

cs.AI2026

MedGemma 1.5 Technical Report

Andrew Sellergren, Chufan Gao, Fereshteh Mahvar +39

We introduce MedGemma 1.5 4B, the latest model in the MedGemma collection. MedGemma 1.5 expands on MedGemma 1 by integrating additional capabilities: high-dimensional medical imagi…

cs.HC2026★ 1 cited

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…

cs.AI2025★ 41 cited

MedGemma Technical Report

Andrew Sellergren, Sahar Kazemzadeh, Tiam Jaroensri +78

Artificial intelligence (AI) has significant potential in healthcare applications, but its training and deployment faces challenges due to healthcare's diverse data, complex tasks,…

cs.CL2025

Advancing Conversational Diagnostic AI with Multimodal Reasoning

Khaled Saab, Jan Freyberg, Chunjong Park +33

Large Language Models (LLMs) have demonstrated great potential for conducting diagnostic conversations but evaluation has been largely limited to language-only interactions, deviat…

cs.AI2025★ 4 cited

TxGemma: Efficient and Agentic LLMs for Therapeutics

Eric Wang, Samuel Schmidgall, Paul F. Jaeger +6

Therapeutic development is a costly and high-risk endeavor that is often plagued by high failure rates. To address this, we introduce TxGemma, a suite of efficient, generalist larg…

cs.CL2025★ 3 cited

Towards Conversational AI for Disease Management

Anil Palepu, Valentin Liévin, Wei-Hung Weng +17

While large language models (LLMs) have shown promise in diagnostic dialogue, their capabilities for effective management reasoning - including disease progression, therapeutic res…

cs.HC2024

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…

cs.HC2024★ 3 cited

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…

cs.CV2024★ 30 cited

Advancing Multimodal Medical Capabilities of Gemini

Lin Yang, Shawn Xu, Andrew Sellergren +44

Many clinical tasks require an understanding of specialized data, such as medical images and genomics, which is not typically found in general-purpose large multimodal models. Buil…

cs.AI2024★ 96 cited

Capabilities of Gemini Models in Medicine

Khaled Saab, Tao Tu, Wei-Hung Weng +64

Excellence in a wide variety of medical applications poses considerable challenges for AI, requiring advanced reasoning, access to up-to-date medical knowledge and understanding of…

cs.CY2024★ 99 cited

A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models

Stephen R. Pfohl, Heather Cole-Lewis, Rory Sayres +27

Large language models (LLMs) hold promise to serve complex health information needs but also have the potential to introduce harm and exacerbate health disparities. Reliably evalua…

cs.AI2024★ 100 cited

Towards Conversational Diagnostic AI

Tao Tu, Anil Palepu, Mike Schaekermann +22

At the heart of medicine lies the physician-patient dialogue, where skillful history-taking paves the way for accurate diagnosis, effective management, and enduring trust. Artifici…

cs.CY2023★ 63 cited

Towards Accurate Differential Diagnosis with Large Language Models

Daniel McDuff, Mike Schaekermann, Tao Tu +25

An accurate differential diagnosis (DDx) is a cornerstone of medical care, often reached through an iterative process of interpretation that combines clinical history, physical exa…