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Not the Models You Are Looking For: Traditional ML Outperforms LLMs in Clinical Prediction Tasks

2024-12-05

Abstract excerpt

<h4>ABSTRACT</h4> <h4>Objectives</h4> To determine the extent to which current Large Language Models (LLMs) can serve as substitutes for traditional machine learning (ML) as clinical predictors using data from electronic health records (EHRs), we investigated various factors that can impact their adoption, including overall performance, calibration, fairness, and resilience to privacy protections that reduce data...

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Literature Corpus work
f3edb16d-06e7-52ba-a21d-0cfb93f39e0d
DOI
10.1101/2024.12.03.24318400
Open publication

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Not the Models You Are Looking For: Traditional ML Outperforms LLMs in Clinical Prediction TasksDOI 10.1101/2024.12.03.24318400
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