Predizione del tipo di mutazione nelle malattie mitocondriali primarie tramite modelli di machine learning applicati a dati clinici non genetici né istologici.

Abstract

This study shows that machine learning can accurately distinguish between mitochondrial and nuclear DNA mutations in primary mitochondrial diseases using only non-genetic and non-histological clinical data. While language models underperform in comparison, they show potential as complementary diagnostic tools.