MedFeat: Model-Aware and Explainability-Driven Feature Engineering with LLMs for Tabular Prediction

arXiv:2603.02221 · cs.LG, cs.AI · Submitted 2026-02-10 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-02-10

Updated: 2026-10-01

Code: https://github.com/zizhengzhang1/MedFeat

Terminology

• Feature Engineering — 3× in this paper · explained in 3 episodes
• Explainability — 1× in this paper · explained in 3 episodes
• Interpretability — 1× in this paper · explained in 15 episodes

Sources

• LLM-FE: Automated Feature Engineering for Tabular Data with LLMs as Evolutionary Optimizers
• Large Language Models Can Automatically Engineer Features for Few-Shot Tabular Learning
• GPT-4o System Card
• Does Deep Learning REALLY Outperform Non-deep Machine Learning for Clinical Prediction on Physiological Time Series?

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