Summary of Agentmd: Empowering Language Agents For Risk Prediction with Large-scale Clinical Tool Learning, by Qiao Jin et al.
AgentMD: Empowering Language Agents for Risk Prediction with Large-Scale Clinical Tool Learning
by Qiao Jin, Zhizheng Wang, Yifan Yang, Qingqing Zhu, Donald Wright, Thomas Huang, W John Wilbur, Zhe He, Andrew Taylor, Qingyu Chen, Zhiyong Lu
First submitted to arxiv on: 20 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper introduces AgentMD, a novel language agent that can automatically curate and apply clinical calculators across various clinical contexts. By leveraging large language models and extensive collections of clinical calculators, AgentMD aims to overcome the obstacles hindering their widespread utilization in healthcare. The study demonstrates the potential of AgentMD by curating a collection of 2,164 diverse clinical calculators with executable functions and structured documentation, achieving an accuracy of over 80% on three quality metrics through manual evaluations. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary In simple terms, this paper is about using artificial intelligence to help doctors make better predictions for patients. It’s like having a super smart assistant that can find the right calculator or tool to use in different situations. The researchers created something called AgentMD that can take in information about a patient and then pick the best calculator to use based on that information. They tested it with real-world clinical notes and found it was very accurate. |
