4 papers
Towards symbolic regression for interpretable clinical decision scores
Guilherme Seidyo Imai Aldeia, Joseph D. Romano, Fabricio Olivetti de Franca +2
Medical decision-making makes frequent use of algorithms that combine risk equations with rules, providing clear and standardized treatment pathways. Symbolic regression (SR) tradi…
Current Challenges of Symbolic Regression: Optimization, Selection, Model Simplification, and Benchmarking
Guilherme Seidyo Imai Aldeia
Symbolic Regression (SR) is a regression method that aims to discover mathematical expressions that describe the relationship between variables, and it is often implemented through…
Iterative Learning of Computable Phenotypes for Treatment Resistant Hypertension using Large Language Models
Guilherme Seidyo Imai Aldeia, Daniel S. Herman, William G. La Cava
Large language models (LLMs) have demonstrated remarkable capabilities for medical question answering and programming, but their potential for generating interpretable computable p…
Interaction-Transformation Evolutionary Algorithm for Symbolic Regression
Fabricio Olivetti de Franca, Guilherme Seidyo Imai Aldeia
The Interaction-Transformation (IT) is a new representation for Symbolic Regression that restricts the search space into simpler, but expressive, function forms. This representatio…