335 citations · 977 across the 22 of their papers we have counts for
24 papers
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…
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…
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…
SymptomAI: Toward a Conversational AI Agent for Everyday Symptom Assessment
Joseph Breda, Fadi Yousif, Beszel Hawkins +30
Language models excel at diagnostic assessments on curated medical case-studies and vignettes, performing on par with, or better than, clinical professionals. However, existing stu…
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…
Complementary Human-AI Clinical Reasoning in Ophthalmology
Mertcan Sevgi, Fares Antaki, Abdullah Zafar Khan +26
Vision impairment and blindness are a major global health challenge where gaps in the ophthalmology workforce limit access to specialist care. We evaluate AMIE, a medically fine-tu…
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…
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Gheorghe Comanici, Eric Bieber, Mike Schaekermann +3431
In this report, we introduce the Gemini 2.X model family: Gemini 2.5 Pro and Gemini 2.5 Flash, as well as our earlier Gemini 2.0 Flash and Flash-Lite models. Gemini 2.5 Pro is our…
MedPAIR: Measuring Physicians and AI Relevance Alignment in Medical Question Answering
Yuexing Hao, Kumail Alhamoud, Hyewon Jeong +6
Large Language Models (LLMs) have demonstrated remarkable performance on various medical question-answering (QA) benchmarks, including standardized medical exams. However, correct…
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…
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…
LearnLM: Improving Gemini for Learning
LearnLM Team, Abhinit Modi, Aditya Srikanth Veerubhotla +43
Today's generative AI systems are tuned to present information by default, rather than engage users in service of learning as a human tutor would. To address the wide range of pote…
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…
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…
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…
MINT: A wrapper to make multi-modal and multi-image AI models interactive
Jan Freyberg, Abhijit Guha Roy, Terry Spitz +10
During the diagnostic process, doctors incorporate multimodal information including imaging and the medical history - and similarly medical AI development has increasingly become m…
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…
Consensus, dissensus and synergy between clinicians and specialist foundation models in radiology report generation
Ryutaro Tanno, David G. T. Barrett, Andrew Sellergren +23
Radiology reports are an instrumental part of modern medicine, informing key clinical decisions such as diagnosis and treatment. The worldwide shortage of radiologists, however, re…
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…
Towards Generalist Biomedical AI
Tao Tu, Shekoofeh Azizi, Danny Driess +29
Medicine is inherently multimodal, with rich data modalities spanning text, imaging, genomics, and more. Generalist biomedical artificial intelligence (AI) systems that flexibly en…
Evaluating AI systems under uncertain ground truth: a case study in dermatology
David Stutz, Ali Taylan Cemgil, Abhijit Guha Roy +17
For safety, medical AI systems undergo thorough evaluations before deployment, validating their predictions against a ground truth which is assumed to be fixed and certain. However…
Towards Expert-Level Medical Question Answering with Large Language Models
Karan Singhal, Tao Tu, Juraj Gottweis +28
Recent artificial intelligence (AI) systems have reached milestones in "grand challenges" ranging from Go to protein-folding. The capability to retrieve medical knowledge, reason o…
Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photos
Sonia Phene, R. Carter Dunn, Naama Hammel +17
Glaucoma is the leading cause of preventable, irreversible blindness world-wide. The disease can remain asymptomatic until severe, and an estimated 50%-90% of people with glaucoma…