Applications of Artificial Intelligence in the Neuropsychological Assessment of Dementia: A Systematic Review.
artificial intelligence
dementia
machine learning
mild cognitive impairment
neuropsychological assessment
Journal
Journal of personalized medicine
ISSN: 2075-4426
Titre abrégé: J Pers Med
Pays: Switzerland
ID NLM: 101602269
Informations de publication
Date de publication:
19 Jan 2024
19 Jan 2024
Historique:
received:
18
12
2023
revised:
09
01
2024
accepted:
16
01
2024
medline:
26
1
2024
pubmed:
26
1
2024
entrez:
26
1
2024
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 38276235
pii: jpm14010113
doi: 10.3390/jpm14010113
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng