AIMC Topic: Mental Status and Dementia Tests
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A distributed multitask multimodal approach for the prediction of Alzheimer's disease in a longitudinal study.
NeuroImage
Nov 1, 2019
Predicting the progression of Alzheimer's Disease (AD) has been held back for decades due to the lack of sufficient longitudinal data required for the development of novel machine learning algorithms. This study proposes a novel machine learning algo...
Optimized machine learning methods for prediction of cognitive outcome in Parkinson's disease.
Computers in biology and medicine
Jun 28, 2019
BACKGROUND: Given the increasing recognition of the significance of non-motor symptoms in Parkinson's disease, we investigate the optimal use of machine learning methods for the prediction of the Montreal Cognitive Assessment (MoCA) score at year 4 f...
Studying the Manifold Structure of Alzheimer's Disease: A Deep Learning Approach Using Convolutional Autoencoders.
IEEE journal of biomedical and health informatics
Jun 17, 2019
Many classical machine learning techniques have been used to explore Alzheimer's disease (AD), evolving from image decomposition techniques such as principal component analysis toward higher complexity, non-linear decomposition algorithms. With the a...
Harnessing the Power of Machine Learning in Dementia Informatics Research: Issues, Opportunities, and Challenges.
IEEE reviews in biomedical engineering
Mar 12, 2019
Dementia is a chronic and degenerative condition affecting millions globally. The care of patients with dementia presents an ever-continuing challenge to healthcare systems in the 21st century. Medical and health sciences have generated unprecedented...
Ensemble support vector machine classification of dementia using structural MRI and mini-mental state examination.
Journal of neuroscience methods
Feb 3, 2018
BACKGROUND: The International Challenge for Automated Prediction of MCI from MRI data offered independent, standardized comparison of machine learning algorithms for multi-class classification of normal control (NC), mild cognitive impairment (MCI), ...
Looking for Alzheimer's Disease morphometric signatures using machine learning techniques.
Journal of neuroscience methods
Nov 22, 2017
BACKGROUND: We present our results in the International challenge for automated prediction of MCI from MRI data. We evaluate the performance of MRI-based neuromorphometrics features (nMF) in the classification of Healthy Controls (HC), Mild Cognitive...
Classification of patients with MCI and AD from healthy controls using directed graph measures of resting-state fMRI.
Behavioural brain research
Jun 23, 2016
Brain network alterations in patients with Alzheimer's disease (AD) has been the subject of much investigation, but the biological mechanisms underlying these alterations remain poorly understood. Here, we aim to identify the changes in brain network...
Development of Machine-Learning-Based Models for Detection of Cognitive Impairment in Patients Receiving Maintenance Hemodialysis.
European journal of neurology
Jun 1, 2025
BACKGROUND: Cognitive impairment is common but frequently undiagnosed in the dialysis population. We aimed to develop and validate a quick and accurate screening tool using machine-learning-based approaches in them.
Mini-mental status examination phenotyping for Alzheimer's disease patients using both structured and narrative electronic health record features.
Journal of the American Medical Informatics Association : JAMIA
Jan 1, 2025
OBJECTIVE: This study aims to automate the prediction of Mini-Mental State Examination (MMSE) scores, a widely adopted standard for cognitive assessment in patients with Alzheimer's disease, using natural language processing (NLP) and machine learnin...
Importance of Serum Albumin in Deep Learning-Based Prediction of Cognitive Function Data in the Aged Using a Basic Blood Test.
Advances in experimental medicine and biology
Jan 1, 2024
BACKGROUND: Recently, a method using deep learning has been developed to estimate the risk of developing dementia. This method uses general blood test data from routine health examinations that reveal lifestyle-related diseases, which can lead to vas...
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