Permutation-calibrated stability discovery under ???? >> ????: A leak-controlled Machine Learning framework identifies candidate proteomics panels in antiseizure medication-related side effects
This study introduces a leak-controlled machine learning framework that utilizes permutation-calibrated stability selection to identify robust candidate proteomics panels associated with antiseizure medication-related CNS side effects in epilepsy patients, revealing immune and inflammatory pathways as key modulators while overcoming the limitations of standard multiple testing in high-dimensional, low-sample datasets.