activity
20232026
most citedTowards Conversational Diagnostic AI

100 citations · 326 across the 11 of their papers we have counts for

collaborators

15 papers

cs.CY2026

Harnessing Generative UI for Education: Tailored Learning Interactives

Alisa Kovshov, Anisha Choudhury, Anna Iurchenko +26

It is well established that students learn best through active engagement, particularly via interactive experiences tied to real-world concepts. Creating such experiences, however,…

cs.HC2026

Towards Scalable Measurement of Durable Skills

Amir Globerson, Amy Keeling, Anisha Choudhury +37

Durable skills, such as collaboration, creativity and critical thinking, are instrumental to success in the modern workforce. Yet, measuring these skills remains a persistent chall…

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.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.CY2025★ 1 cited

Towards an AI-Augmented Textbook

LearnLM Team, Google, : +34

Textbooks are a cornerstone of education, but they have a fundamental limitation: they are a one-size-fits-all medium. Any new material or alternative representation requires arduo…

cs.AI2025

An AI system to help scientists write expert-level empirical software

Eser Aygün, Anastasiya Belyaeva, Gheorghe Comanici +39

The cycle of scientific discovery is frequently bottlenecked by the slow, manual creation of software to support computational experiments\cite{hannay2009how}. To address this, we…

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.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.AI2025★ 87 cited

Accelerating scientific discovery with Co-Scientist

Juraj Gottweis, Wei-Hung Weng, Alexander Daryin +48

Scientific discovery is driven by scientists generating novel hypotheses for complex problems that undergo rigorous experimental validation. To augment this process, we introduce C…

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…

eess.IV2024

Closing the AI generalization gap by adjusting for dermatology condition distribution differences across clinical settings

Rajeev V. Rikhye, Aaron Loh, Grace Eunhae Hong +23

Recently, there has been great progress in the ability of artificial intelligence (AI) algorithms to classify dermatological conditions from clinical photographs. However, little i…

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…