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Iterative Learning of Computable Phenotypes for Treatment Resistant Hypertension using Large Language Models.
0
Zitationen
3
Autoren
2025
Jahr
Abstract
strategy that uses LLMs to generate and iteratively refine CPs using data-driven feedback. Our results show that LLMs, coupled with iterative learning, can generate interpretable and reasonably accurate programs that approach the performance of state-of-the-art ML methods while requiring significantly fewer training examples.
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