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papersTODAY 04:00 UTC

Study Compares LLM-Generated Rules With Traditional Models for Heart Disease Prediction

A new arXiv paper evaluates rule-based systems produced by large language models against conventional machine learning classifiers for predicting heart disease. Using the UCI Heart Disease dataset, the authors benchmark models including logistic regression and k-nearest neighbors. The work examines whether LLM-derived decision rules can match or complement established clinical prediction methods.

arXiv Logistic regression k-nearest-neighbors heart-disease-prediction large-language-models machine-learning

COVERAGE · 1 REPORT · LINKS GO TO THE ORIGINAL OUTLETS

arXiv cs.LGEvaluating LLM-Generated Rules for Heart Disease Prediction ↗TODAY 04:00 UTC