Abstract
Introduction: Artificial intelligence (AI) has emerged as a relevant tool in neuropsychology, with potential to optimize clinical, research, and educational processes.
Materials and Methods: A theoretical review was conducted using databases such as PubMed, Scopus, ScienceDirect, Scielo, and Redalyc, applying MeSH terms and Boolean operators. Articles in English and Spanish, mainly from 2014 onward, were included. Of 98 records, 52 were selected after applying eligibility criteria.
Results: Three domains of application were identified: clinical, research, and educational. In clinical settings, AI achieved diagnostic accuracies of up to 91% in dementia prediction and supported neuroimaging analysis and treatment. In research, it enabled large-scale data analysis, biomarker identification, and predictive modeling. In education, it showed benefits in personalized learning, although with lower levels of evidence.
Discussion: Limitations include low interpretability, generalizability issues, and ethical challenges related to bias and data privacy.
Conclusions: AI represents a significant advancement in neuropsychology but requires ethical-legal frameworks and should complement, not replace, clinical expertise.
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