USE OF ARTIFICIAL INTELLIGENCE IN THE DIAGNOSIS OF NEURODEGENERATIVE DISEASES: AN INTEGRATIVE REVIEW
DOI:
https://doi.org/10.53612/recisatec.v2i10.196Keywords:
Artificial intelligence; Neurodegenerative; Diagnosis.Abstract
Neurodegenerative diseases (NDs) are debilitating, incurable diseases that cause progressive and irreversible loss of neurons and other brain cells, and cause functional changes in the central nervous system (CNS), affecting movement and body function. This research aims to describe the use of artificial intelligence (AI) in the diagnosis of neurodegenerative diseases. This is descriptive research of the integrative literature review type. The search was carried out through online access to the Virtual Health Library (VHL) database, indexed in the Medical Literature Analysis and Retrieval System Online (MEDLINE) database. To search for the works, the keywords present in the Medical Subject Headings (MeSH) were used, they were: Artificial intelligence AND Neurodegenerative AND Diagnosis. The results showed that the most used AI tools in the diagnosis of neurodegenerative diseases are imaging biomarkers (positron emission tomography (PET) and single photon emission computed tomography (SPECT), in addition to Computer-Aided Design (CAD), machine learning, in English – Machine Learning (ML), use of Deep Learning (DL) applications. It was concluded that AI is an important tool for the diagnosis of neurodegenerative diseases, because, as demonstrated in the literature, the artificial intelligence reduces time, improves the accuracy and reliability of the diagnosis of neurodegenerative diseases.
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