Evaluating the use of large language models to provide clinical recommendations in the Emergency Department

Nature·Oct 8

✦ NabkaNews BriefAuto-summarized from multiple outlets · verify with the source

Researchers are evaluating the use of large language models to provide clinical recommendations in emergency departments. The evaluations are being conducted through various approaches, including adversarial testing and benchmarking, to assess the safety and competencies of these models in healthcare settings. Studies are also comparing the performance of large language models to human researchers on complex medical queries, although the focus and scope of these evaluations appear to be broad and multifaceted.

Full coverage

Evaluating the safety of large language models in healthcare and dentistry: adversarial testing approaches

Nature·5d ago

Open-source solution for evaluation and benchmarking of large language models for public health

medRxiv·Oct 8

Evaluating clinical competencies of large language models with a general practice benchmark

Nature·Apr 16

LLM-as-a-Judge: What It Is, Why It Works, and How to Use It to Evaluate AI Models

Towards Data Science·Nov 24

Evaluating large language models for AI-assisted grading: a framework and case study in higher education

Nature·Apr 18

ClinicRealm: Re-evaluating large language models with conventional machine learning for non-generative clinical prediction tasks

Nature·Apr 8

Evaluating multimodal commercial and open-source large language models for dynamical astronomy: a benchmark study of resonant behavior classification

Nature·Mar 28

Evaluating the performance of large language models versus human researchers on real world complex medical queries

Nature·Oct 29

View original report at Nature ↗

Fetching the latest headlines…