AIMC Topic: Apolipoproteins E

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Optimizing Machine Learning Methods to Improve Predictive Models of Alzheimer's Disease.

Journal of Alzheimer's disease : JAD Jan 1, 2019
BACKGROUND: Predicting clinical course of cognitive decline can boost clinical trials' power and improve our clinical decision-making. Machine learning (ML) algorithms are specifically designed for the purpose of prediction; however. identifying opti...
Humans Machine Learning Prognosis Female Aged Aged, 80 and over Male Middle Aged Cognitive Dysfunction Support Vector Machine Longitudinal Studies Magnetic Resonance Imaging Models, Neurological Predictive Value of Tests Discriminant Analysis Alzheimer Disease Hippocampus Cerebral Cortex Apolipoproteins E Demography
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Development of a Late-Life Dementia Prediction Index with Supervised Machine Learning in the Population-Based CAIDE Study.

Journal of Alzheimer's disease : JAD Jan 1, 2017
BACKGROUND AND OBJECTIVE: This study aimed to develop a late-life dementia prediction model using a novel validated supervised machine learning method, the Disease State Index (DSI), in the Finnish population-based CAIDE study.
Humans Retrospective Studies Female Reproducibility of Results Risk Factors Aged Male Severity of Illness Index Dementia ROC Curve Cognition Predictive Value of Tests Supervised Machine Learning Cerebrovascular Disorders Neuropsychological Tests Finland Apolipoproteins E Community Health Planning
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