Using Symbolic Regression for Interpretable Healthcare Machine Learning

Symbolic regression is introduced as a method to enhance interpretability in machine learning applications within healthcare. This approach helps create models that are more understandable by humans, facilitating better decision-making and trust in AI-driven healthcare solutions. The technique aims to balance predictive accuracy with transparency, addressing challenges in medical data analysis and patient care.

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