Multi-Layer Insight into Neurodegenerative Diseases: Big Data and AI Perspectives

The study of neurodegenerative diseases has thus given artificial intelligence an opportunity to solve traditional problems within the context of the big data era. Most neurodegenerative disorders are associated with complex genetic fingerprints that are currently the center of intense contemporary study. Multiomic data, when combined with neuroimaging and electronic health record data, might become important in making the most detailed patient profile workable. Deep learning will make it feasible to generate intractable profiles for early pathologic diagnosis, better treatment personalization, and valuable insights into neurodegenerative diseases for drug development and repurposing. In this sense, this paper delves into how relevant research has sought to demonstrate with the available data sources in biomedicine that deep learning may play a pivotal role in getting a more precise understanding of the mechanisms behind neurodegenerative diseases such as Alzheimer’s and Parkinson’s. Diseases that are associated with a neurodegenerative course, like Alzheimer’s, Parkinson’s, and amyotrophic lateral sclerosis (ALS), create complex challenges because of their multifactorial etiologies and heterogeneous pathologies. The birth of big data and artificial intelligence (AI) has inexorably shifted the landscape of research on neurodegenerative disorders through innovative insights and opportunities for the understanding of these conditions. This abstract investigates the multi-layered approach to neurodegenerative diseases facilitated by big data and AI. AI uses vast datasets from genomics, proteomics, neuroimaging, and clinical records to develop machine learning and deep learning skills to recognize patterns and relationships, predict disease progression, and find new biomarkers and therapeutic targets. Major findings include considerably improved diagnostic accuracy, personalized therapeutic approaches, and identification of disease mechanisms that are now known to be driven by artificial intelligence analyses.