AI and Neurodegenerative Diseases: Advancing Diagnosis and Treatment

Abstract

The complex pathophysiology, progressive nature, and lack of effective therapies, neurodegenerative disorders like Alzheimer's disease, Parkinson's disease, Huntington's disease, and Amyotrophic Lateral Sclerosis (ALS) pose serious difficulties to healthcare systems around the world. These conditions cause a steady reduction in cognitive and motor abilities, which hurts patients' quality of life and puts a heavy load on caregivers and medical professionals. Overlapping symptoms, early detection, and long-term disease progression monitoring frequently challenge the diagnosis and treatment of neurodegenerative disorders. Artificial Intelligence (AI) is being used increasingly to improve neurodegenerative disease diagnosis, monitoring, and therapy, opening up new avenues for patient outcomes and care quality. An extensive summary of the existing and future uses of AI in the treatment of neurodegenerative illnesses is given in this paper. It examines how Artificial Intelligence (AI) is advancing neuroimaging, including the application of machine learning algorithms to early identification of structural and functional alterations in the brain linked to various disorders. Artificial Intelligence (AI)-enabled personalized treatment options are explored, emphasizing how AI algorithms can forecast patient reactions to medicines, optimize treatment plans, and assist in creating focused interventions. A critical assessment of the shortcomings of existing AI technologies, including issues with data privacy, algorithmic bias, and the requirement for strong clinical validation to guarantee the security and effectiveness of AI applications in clinical practice, round out the review. Notwithstanding these obstacles, Artificial Intelligence has enormous promise to transform the treatment of neurodegenerative illnesses in the future.