most citedAccelerating scientific discovery with Co-Scientist

76 citations · 76 across the 3 of their papers we have counts for

collaborators

9 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.AI202676 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.AI2026

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.AI2026

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.HC2026

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…