Researchers from the University of Texas at Arlington have developed an AI algorithm to provide personalized treatment options for esophageal cancer patients. This algorithm, detailed in a study published in the Journal of Mathematical Biology, is designed to address the disease’s heterogeneity and guide treatment by using a pharmacokinetic model to determine ideal drug doses, conducting sensitivity analysis to identify factors influencing cancer progression, and applying an optimal control model for selecting drug combinations and dosages.
The framework, tested with synthetic data, has shown high accuracy in recommending optimal treatment strategies, offering a new tool for clinicians in the fight against esophageal cancer.