A Computational Approach to Epilepsy Treatment: An AI-optimized Global Natural Product Prescription System

TL;DR

This paper presents an AI-driven system that analyzes global natural products and clinical trial data to optimize herbal treatments for epilepsy, demonstrating improved seizure reduction over conventional methods.

Contribution

The study introduces a novel computational framework combining machine learning, Bayesian optimization, and meta-analysis to personalize herbal epilepsy therapy.

Findings

Identified 17 high-efficacy herbs with significant seizure reduction

AI-optimized prescriptions led to 28.5% greater seizure reduction in validation trial

System integrates data from 48 RCTs and 1,872 compounds for evidence-based recommendations

Abstract

Epilepsy is a prevalent neurological disease with millions of patients worldwide. Many patients have turned to alternative medicine due to the limited efficacy and side effects of conventional antiepileptic drugs. In this study, we developed a computational approach to optimize herbal epilepsy treatment through AI-driven analysis of global natural products and statistically validated randomized controlled trials (RCTs). Our intelligent prescription system combines machine learning (ML) algorithms for herb-efficacy characterization, Bayesian optimization for personalized dosing, and meta-analysis of RCTs for evidence-based recommendations. The system analyzed 1,872 natural compounds from traditional Chinese medicine (TCM), Ayurveda, and ethnopharmacological databases, integrating their bioactive properties with clinical outcomes from 48 RCTs covering 48 epilepsy conditions (n=5,216). Using LASSO regression and SHAP value analysis, we identified 17 high-efficacy herbs (e.g., Gastrodia elata [using \'e for accented characters], Withania somnifera), showing significant seizure reduction (p$<$0.01, Cohen's d=0.89) with statistical significance confirmed by multiple testing (p$<$0.001). A randomized double-blind validation trial (n=120) demonstrated 28.5\% greater seizure frequency reduction with AI-optimized herbal prescriptions compared to conventional protocols (95\% CI: 18.7-37.3\%, p=0.003).