Rethinking Dementia Risk Prediction: A Critical Evaluation of a Multimodal Machine Learning Predictive Model.
J Alzheimers Dis
; 97(3): 1097-1100, 2024.
Article
in En
| MEDLINE
| ID: mdl-38189753
ABSTRACT
A recent study by Ding et al. explores the integration of artificial intelligence (AI) in predicting dementia risk over a 10-year period using a multimodal approach. While revealing the potential of machine learning models in identifying high-risk individuals through neuropsychological testing, MRI imaging, and clinical risk factors, the imperative of dynamic frailty assessment emerges for accurate late-life dementia prediction. The commentary highlights challenges associated with AI models, including dimensionality and data standardization, emphasizing the critical need for a dynamic, comprehensive approach to reflect the evolving nature of dementia and improve predictive accuracy.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Dementia
/
Frailty
Type of study:
Etiology_studies
/
Prognostic_studies
/
Risk_factors_studies
Limits:
Humans
Language:
En
Journal:
J Alzheimers Dis
Journal subject:
GERIATRIA
/
NEUROLOGIA
Year:
2024
Document type:
Article
Affiliation country:
Italy