activity
20232026
most citedCapabilities of Gemini Models in Medicine

96 citations · 284 across the 18 of their papers we have counts for

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Showing 2024Show all

12 papers · 1 filter

cs.CL2024★ 1 cited

A Demonstration of Adaptive Collaboration of Large Language Models for Medical Decision-Making

Yubin Kim, Chanwoo Park, Hyewon Jeong +7

Medical Decision-Making (MDM) is a multi-faceted process that requires clinicians to assess complex multi-modal patient data patient, often collaboratively. Large Language Models (…

cs.CV2024

SympCam: Remote Optical Measurement of Sympathetic Arousal

Björn Braun, Daniel McDuff, Tadas Baltrusaitis +3

Recent work has shown that a person's sympathetic arousal can be estimated from facial videos alone using basic signal processing. This opens up new possibilities in the field of t…

cs.LG2024★ 5 cited

Scaling Wearable Foundation Models

Girish Narayanswamy, Xin Liu, Kumar Ayush +15

Wearable sensors have become ubiquitous thanks to a variety of health tracking features. The resulting continuous and longitudinal measurements from everyday life generate large vo…

cs.CV2024★ 1 cited

PARSE-Ego4D: Personal Action Recommendation Suggestions for Egocentric Videos

Steven Abreu, Tiffany D. Do, Karan Ahuja +4

Intelligent assistance involves not only understanding but also action. Existing ego-centric video datasets contain rich annotations of the videos, but not of actions that an intel…

cs.AI2024★ 13 cited

Towards a Personal Health Large Language Model

Justin Cosentino, Anastasiya Belyaeva, Xin Liu +31

In health, most large language model (LLM) research has focused on clinical tasks. However, mobile and wearable devices, which are rarely integrated into such tasks, provide rich,…

cs.LG2024★ 4 cited

The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources

Shayne Longpre, Stella Biderman, Alon Albalak +20

Foundation model development attracts a rapidly expanding body of contributors, scientists, and applications. To help shape responsible development practices, we introduce the Foun…

cs.AI2024★ 8 cited

Transforming Wearable Data into Personal Health Insights using Large Language Model Agents

Mike A. Merrill, Akshay Paruchuri, Naghmeh Rezaei +17

Deriving personalized insights from popular wearable trackers requires complex numerical reasoning that challenges standard LLMs, necessitating tool-based approaches like code gene…

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.CL2024★ 9 cited

MDAgents: An Adaptive Collaboration of LLMs for Medical Decision-Making

Yubin Kim, Chanwoo Park, Hyewon Jeong +7

Foundation models are becoming valuable tools in medicine. Yet despite their promise, the best way to leverage Large Language Models (LLMs) in complex medical tasks remains an open…

eess.IV2024★ 1 cited

How Suboptimal is Training rPPG Models with Videos and Targets from Different Body Sites?

Björn Braun, Daniel McDuff, Christian Holz

Remote camera measurement of the blood volume pulse via photoplethysmography (rPPG) is a compelling technology for scalable, low-cost, and accessible assessment of cardiovascular i…

cs.SE2024★ 2 cited

On the Standardization of Behavioral Use Clauses and Their Adoption for Responsible Licensing of AI

Daniel McDuff, Tim Korjakow, Scott Cambo +9

Growing concerns over negligent or malicious uses of AI have increased the appetite for tools that help manage the risks of the technology. In 2018, licenses with behaviorial-use c…

cs.CL2024★ 30 cited

Health-LLM: Large Language Models for Health Prediction via Wearable Sensor Data

Yubin Kim, Xuhai Xu, Daniel McDuff +2

Large language models (LLMs) are capable of many natural language tasks, yet they are far from perfect. In health applications, grounding and interpreting domain-specific and non-l…