ARTIFICIAL INTELLIGENCE IN EARLY DIAGNOSIS OF NEURODEGENERATIVE DISEASES: CURRENT EVIDENCE AND PROSPECTS
Abstract
Neurodegenerative diseases, including Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS), represent a growing global health burden, with millions of individuals affected worldwide and limited disease-modifying therapies available. Early and accurate diagnosis is critical for improving patient outcomes, yet conventional diagnostic approaches often fail to detect pathological changes prior to overt symptom onset. Artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL) methodologies, has demonstrated remarkable promise in transforming early diagnostic paradigms through the analysis of neuroimaging, genetic, clinical, and digital biomarker data.
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