The use of Artificial Intelligence in Parkinson’s Disease
DOI:
https://doi.org/10.33448/rsd-v14i1.48011Keywords:
Artficial Intelligence, Parkinson's Disease, Diagnosis, Treatment.Abstract
Parkinson's disease (PD) is a neurological disorder that degrades the substantia nigra of the brain, causing motor deficits in the individual. Its diffuse symptoms affect clinical analysis, making early diagnosis and treatment difficult. The objective of this study is to analyze the use of artificial intelligence in the diagnosis and treatment of Parkinson's disease. The methodology used was an integrative literature review based on articles published between 2019 and 2024. Significant advances were identified in using machine learning (ML) algorithms for early diagnosis, symptom monitoring, and treatment personalization. Techniques such as convolutional neural networks, biomarker analysis, Internet of Things (IoT) devices, computer-assisted diagnosis (CAD), and WGCNA stood out for their accuracy and efficiency in recognizing PD patterns. Although AI shows great potential in this diagnosis and monitoring, advances in treatment remain limited. Considering the topic's relevance, the development of additional studies for integrating these technologies into clinical practice is indicated.
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Copyright (c) 2025 Eduardo Henrique Franco Cahú da Silva; Ricardo Teti Vieira ; Gabriela Duarte Nunes ; Tiago Gonçalves Siebra ; Caio Vinícius Gueiros Tabosa; João Magalhães Moura; Pedro Hélio Phaelante Costa Guerra ; Hiago Vitório Castro Lima de Melo; Leilane Helena Andrade Lima; Manuela Barbosa Rodrigues de Souza
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