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Volume 14
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Systematic Review

Applications of Artificial Intelligence in the Neuropsychological Assessment of Dementia: A Systematic Review

by
Isabella Veneziani
1,
Angela Marra
2,
Caterina Formica
2,*,
Alessandro Grimaldi
2,
Silvia Marino
2,
Angelo Quartarone
2 and
Giuseppa Maresca
2
1
Department of Nervous System and Behavioural Sciences, Psychology Section, University of Pavia, Piazza Botta, 11, 27100 Pavia, Italy
2
IRCCS Centro Neurolesi “Bonino-Pulejo”, S.S. 113 Via Palermo C. da Casazza, 98124 Messina, Italy
*
Author to whom correspondence should be addressed.
J. Pers. Med. 2024, 14(1), 113; https://doi.org/10.3390/jpm14010113
Submission received: 18 December 2023 / Revised: 9 January 2024 / Accepted: 16 January 2024 / Published: 19 January 2024
(This article belongs to the Section Epidemiology)
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Abstract

In the context of advancing healthcare, the diagnosis and treatment of cognitive disorders, particularly Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD), pose significant challenges. This review explores Artificial Intelligence (AI) and Machine Learning (ML) in neuropsychological assessment for the early detection and personalized treatment of MCI and AD. The review includes 37 articles that demonstrate that AI could be an useful instrument for optimizing diagnostic procedures, predicting cognitive decline, and outperforming traditional tests. Three main categories of applications are identified: (1) combining neuropsychological assessment with clinical data, (2) optimizing existing test batteries using ML techniques, and (3) employing virtual reality and games to overcome the limitations of traditional tests. Despite advancements, the review highlights a gap in developing tools that simplify the clinician’s workflow and underscores the need for explainable AI in healthcare decision making. Future studies should bridge the gap between technical performance measures and practical clinical utility to yield accurate results and facilitate clinicians’ roles. The successful integration of AI/ML in predicting dementia onset could reduce global healthcare costs and benefit aging societies.
Keywords: artificial intelligence; machine learning; mild cognitive impairment; dementia; neuropsychological assessment artificial intelligence; machine learning; mild cognitive impairment; dementia; neuropsychological assessment

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MDPI and ACS Style

Veneziani, I.; Marra, A.; Formica, C.; Grimaldi, A.; Marino, S.; Quartarone, A.; Maresca, G. Applications of Artificial Intelligence in the Neuropsychological Assessment of Dementia: A Systematic Review. J. Pers. Med. 2024, 14, 113. https://doi.org/10.3390/jpm14010113

AMA Style

Veneziani I, Marra A, Formica C, Grimaldi A, Marino S, Quartarone A, Maresca G. Applications of Artificial Intelligence in the Neuropsychological Assessment of Dementia: A Systematic Review. Journal of Personalized Medicine. 2024; 14(1):113. https://doi.org/10.3390/jpm14010113

Chicago/Turabian Style

Veneziani, Isabella, Angela Marra, Caterina Formica, Alessandro Grimaldi, Silvia Marino, Angelo Quartarone, and Giuseppa Maresca. 2024. "Applications of Artificial Intelligence in the Neuropsychological Assessment of Dementia: A Systematic Review" Journal of Personalized Medicine 14, no. 1: 113. https://doi.org/10.3390/jpm14010113

APA Style

Veneziani, I., Marra, A., Formica, C., Grimaldi, A., Marino, S., Quartarone, A., & Maresca, G. (2024). Applications of Artificial Intelligence in the Neuropsychological Assessment of Dementia: A Systematic Review. Journal of Personalized Medicine, 14(1), 113. https://doi.org/10.3390/jpm14010113

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