Use of artificial intelligence to predict clinical evolution in neurological diseases
DOI:
https://doi.org/10.34024/rnc.2025.v33.19991Keywords:
Artificial intelligence, Clinical prediction, Neurological diseasesAbstract
Introduction. Artificial intelligence (AI) has revolutionized medicine, especially in the diagnosis and treatment of neurological diseases. Its application to the central nervous system (CNS) aids in the prediction, early diagnosis, and prognosis of conditions such as stroke, Alzheimer's, and Parkinson's disease, in addition to contributing to pharmaceutical research. Objective. To evaluate the use of AI for predicting clinical progression in neurological diseases. Method. The research was conducted through an integrative literature review, with data collected from databases such as PubMed and ScienceDirect. Articles published between 2014 and 2025 were selected using descriptors such as "artificial intelligence," "clinical prediction," "neurological diseases," "neurodegenerative," "predictive model," and "machine learning." After screening, 25 studies were included in the analysis. Results. The reviewed studies highlight the growing impact of AI in the diagnosis and prognosis of neurological and cardiovascular diseases, with advances in brain data analysis and biomarker development, such as the monitoring of Parkinson's disease. AI has driven the discovery of CNS-targeted drugs and improved the monitoring of conditions such as stroke and heart diseases through platforms integrated with telemedicine. Despite these advances, challenges related to data quality and clinical validation still need to be addressed for effective implementation. Conclusion. AI has enhanced the diagnosis and treatment of neurological diseases, such as Alzheimer's and Parkinson's, through advanced data analysis and personalized therapies. Despite the challenges, its continuous development promises significant improvements in neurological health.
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Copyright (c) 2025 Adrielly Oliveira Mateus, Karollaynne Drielly Moreira de Souza, Isadora Aires Godinho, Larissa Maria Melo Valadares, Maria Isabel Silva Moreira, Rodrigo Pena Modesto
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Accepted 2025-03-13
Published 2025-04-16
