LLMs Archives - Atropos Health

Answered with Evidence (with updates) – a framework for evaluating whether LLM responses to biomedical questions are founded in evidence.

by Julia Rudo | Sep 5, 2025 | Publications

A paper titled, “Introducing Answered with Evidence – A framework for evaluating whether large language model (LLM) responses to biomedical questions are founded in evidence,” was published in medrxiv by authors affiliated with Atropos Health as an update to a prior...

Atropos Health study ranks AI models by how well they summarize medical research

by Julia Rudo | Aug 13, 2025 | News and Media

“With AI wearing ever-more hats in all kinds of workplaces, researchers are scrambling to devise tests that grade how well the technology actually performs in its myriad roles. In healthcare alone, several new benchmarks aim to gauge AI’s prowess in medical settings....

Introducing Answered with Evidence – A framework for evaluating whether LLM responses to biomedical questions are founded in evidence

by Julia Rudo | Jul 2, 2025 | Cell Case Study, Publications

A paper titled, “Introducing Answered with Evidence – A framework for evaluating whether large language model (LLM) responses to biomedical questions are founded in evidence,” was published in medrxiv by authors affiliated with Atropos Health. Short summary:...

RWESummary: A Framework and Test for Choosing Large Language Models to Summarize Real-World Evidence (RWE) Studies

by Julia Rudo | Jun 24, 2025 | Publications

A paper titled, “RWESummary: A Framework and Test for Choosing Large Language Models to Summarize Real-World Evidence (RWE) Studies,” was published by Atropos Health authors Arjun Mukerji, Michael L. Jackson, Jason Jones, and Neil Sanghavi. Short Summary: Large...

Answering real-world clinical questions using large language model, retrieval-augmented generation, and agentic systems

by Julia Rudo | Jun 10, 2025 | Cell Case Study, Publications

A manuscript titled, “Answering real-world clinical questions using large language model, retrieval-augmented generation, and agentic systems,” was published in Digital Health by authors affiliated with Atropos Health, Stanford University, The Hospital for Sick...

Introducing the Atropos Evidence™ Agent–seamlessly integrating RWE into the clinical workflow.

Answered with Evidence (with updates) – a framework for evaluating whether LLM responses to biomedical questions are founded in evidence.

Atropos Health study ranks AI models by how well they summarize medical research

Introducing Answered with Evidence – A framework for evaluating whether LLM responses to biomedical questions are founded in evidence

RWESummary: A Framework and Test for Choosing Large Language Models to Summarize Real-World Evidence (RWE) Studies

Answering real-world clinical questions using large language model, retrieval-augmented generation, and agentic systems

Solutions

Health Systems

Life Sciences

Technology

Platform

Evidence Generation Tools

Data

About

Resources