Author(s) :

Dr. Shankar C. Patil.

Volume/Issue :

Abstract :

Neurodegenerative diseases such as Alzheimer’s, Parkinson’s, and ALS pose significant global health challenges due to their progressive nature and often late diagnosis. Early detection is crucial for effective intervention and improved patient outcomes, yet current screening methods face limitations in sensitivity, accessibility, and objectivity. Artificial intelligence (AI) offers transformative potential by analyzing complex multimodal data—including neuroimaging, genetic profiles, clinical records, and behavioral metrics—to identify subtle early signs of neurodegeneration. This article explores the fundamentals of AI in medical screening, advances in AI-enhanced imaging analysis, integration of multimodal datasets, and AI-powered cognitive and behavioral assessments. Real-world clinical applications and case studies illustrate the benefits and current challenges of AI deployment, including ethical, legal, and privacy considerations. Future innovations, such as federated learning, wearable biosensors, and explainable AI, promise to further enhance early detection and personalized screening. Responsible development and multidisciplinary collaboration are essential to maximize AI’s impact in proactive neurodegenerative disease management.

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