PROGNOSIS OF NEURODEGENERATIVE DISEASES: ARTIFICIAL INTELLIGENCE IN THE DIAGNOSIS OF ALZHEIMER'S, PARKINSON'S AND MULTIPLE SCLEROSIS

PROGNÓSTICO DE DOENÇAS NEURODEGENERATIVAS: INTELIGÊNCIA ARTIFICIAL NO DIAGNÓSTICO DE ALZHEIMER, PARKINSON E ESCLEROSE MÚLTIPLA

Resumen

Introduction: Neurodegenerative diseases, such as Alzheimer's, Parkinson's, and Multiple Sclerosis, cause progressive loss of neurons and cognitive function. Alzheimer's Disease is the most common, primarily affecting the elderly, while Parkinson's causes motor problems and affects all ethnicities. Multiple Sclerosis has a survival rate of up to 30 years, with age being the primary risk factor. Early diagnosis is challenging due to the high cost of tests, but the use of artificial intelligence in neuroimaging can improve diagnosis and prognosis, offering a better quality of life for patients. Objective: Given the increasing number of neurodegenerative diseases, especially Alzheimer's Disease, this study aimed to evaluate the impact of using artificial intelligence for the diagnosis and prognosis of future patients. Method: This is a literature review on the use of artificial intelligence in neuroimaging for early diagnosis and improved prognosis. Databases such as PubMed and Arxiv were used, with keywords like Alzheimer's, Parkinson's, Multiple Sclerosis, deep learning, and artificial intelligence, covering the years 2014 to 2024. Results: Based on the analysis of selected studies, it was observed that Alzheimer's Disease is the most prevalent pathology in the current population, and artificial intelligence, combined with neuroimaging, can facilitate a more effective and early diagnosis. Conclusion: It was concluded that, although promising, the use of artificial intelligence in neuroimaging still requires extensive research and advancements in this broad field.