Machine learning, artificial intelligence and the prediction of dementia
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Title
Machine learning, artificial intelligence and the prediction of dementia
Authors
Keywords
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Journal
CURRENT OPINION IN PSYCHIATRY
Volume 35, Issue 2, Pages 123-129
Publisher
Ovid Technologies (Wolters Kluwer Health)
Online
2021-12-04
DOI
10.1097/yco.0000000000000768
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Note: Only part of the references are listed.- Automated quantitative MRI volumetry reports support diagnostic interpretation in dementia: a multi-rater, clinical accuracy study
- (2021) Hugh G. Pemberton et al. EUROPEAN RADIOLOGY
- Machine Learning Algorithms and Statistical Approaches for Alzheimer's Disease Analysis based on resting-state EEG Recordings: A Systematic Review
- (2021) Katerina D. Tzimourta et al. International Journal of Neural Systems
- Blinded Clinical Evaluation for Dementia of Alzheimer’s Type Classification Using FDG-PET: A Comparison Between Feature-Engineered and Non-Feature-Engineered Machine Learning Methods
- (2021) Da Ma et al. JOURNAL OF ALZHEIMERS DISEASE
- Personalised predictive modelling with brain-inspired spiking neural networks of longitudinal MRI neuroimaging data and the case study of dementia
- (2021) Maryam Doborjeh et al. NEURAL NETWORKS
- Dementia risks identified by vocal features via telephone conversations: A novel machine learning prediction model
- (2021) Akihiro Shimoda et al. PLoS One
- Cross-cultural validation of the stroke riskometer using generalizability theory
- (2021) Oleg Medvedev et al. Scientific Reports
- Machine learning methods for predicting progression from mild cognitive impairment to Alzheimer’s disease dementia: a systematic review
- (2021) Sergio Grueso et al. Alzheimers Research & Therapy
- Normative brain volume reports may improve differential diagnosis of dementing neurodegenerative diseases in clinical practice
- (2020) Dennis M. Hedderich et al. EUROPEAN RADIOLOGY
- Big data in digital healthcare: lessons learnt and recommendations for general practice
- (2020) Raag Agrawal et al. HEREDITY
- Prevalence and Diagnosis of Neurological Disorders Using Different Deep Learning Techniques: A Meta-Analysis
- (2020) Ritu Gautam et al. JOURNAL OF MEDICAL SYSTEMS
- Predicting Cognitive Impairment and Dementia: A Machine Learning Approach
- (2020) Damaris Aschwanden et al. JOURNAL OF ALZHEIMERS DISEASE
- Deep ensemble learning for Alzheimer's disease classification
- (2020) Ning An et al. JOURNAL OF BIOMEDICAL INFORMATICS
- The Power of EEG to Predict Conversion from Mild Cognitive Impairment and Subjective Cognitive Decline to Dementia
- (2020) Knut Engedal et al. DEMENTIA AND GERIATRIC COGNITIVE DISORDERS
- Machine Learning Applied to Diagnosis of Human Diseases: A Systematic Review
- (2020) Nuria Caballé-Cervigón et al. Applied Sciences-Basel
- Automated age- and sex-specific volumetric estimation of regional brain atrophy: workflow and feasibility
- (2020) Julian Caspers et al. EUROPEAN RADIOLOGY
- Deep neural network models for identifying incident dementia using claims and EHR datasets
- (2020) Vijay S. Nori et al. PLoS One
- Past, present and future EEG in the clinical workup of dementias
- (2020) Thomas Koenig et al. PSYCHIATRY RESEARCH-NEUROIMAGING
- Machine Learning for the Classification of Alzheimer’s Disease and Its Prodromal Stage Using Brain Diffusion Tensor Imaging Data: A Systematic Review
- (2020) Lucia Billeci et al. Processes
- EEG based dementia diagnosis using multi-class support vector machine with motor speed cognitive test
- (2020) Neelam Sharma et al. Biomedical Signal Processing and Control
- A comparison of machine learning methods for survival analysis of high-dimensional clinical data for dementia prediction
- (2020) Annette Spooner et al. Scientific Reports
- Automated cognitive health assessment in smart homes using machine learning
- (2020) Abdul Rehman Javed et al. Sustainable Cities and Society
- Neuropsychiatric symptoms as predictors of conversion from MCI to dementia: a machine learning approach
- (2019) Sabela C. Mallo et al. INTERNATIONAL PSYCHOGERIATRICS
- A novel multi-modal machine learning based approach for automatic classification of EEG recordings in dementia
- (2019) Cosimo Ieracitano et al. NEURAL NETWORKS
- Artificial intelligence approaches to predicting and detecting cognitive decline in older adults: A conceptual review
- (2019) Sarah A. Graham et al. PSYCHIATRY RESEARCH
- Deep learning to detect Alzheimer's disease from neuroimaging: A systematic literature review
- (2019) Mr Amir Ebrahimighahnavieh et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- The Global Burden of Mental, Neurological and Substance Use Disorders: An Analysis from the Global Burden of Disease Study 2010
- (2015) Harvey A. Whiteford et al. PLoS One
- Optum Labs: Building A Novel Node In The Learning Health Care System
- (2014) Paul J. Wallace et al. HEALTH AFFAIRS
- MIRIAD—Public release of a multiple time point Alzheimer's MR imaging dataset
- (2012) Ian B. Malone et al. NEUROIMAGE
- The Alzheimer's Disease Neuroimaging Initiative: Progress report and future plans
- (2010) Michael W. Weiner et al. Alzheimers & Dementia
- The Sydney Memory and Ageing Study (MAS): methodology and baseline medical and neuropsychiatric characteristics of an elderly epidemiological non-demented cohort of Australians aged 70–90 years
- (2010) Perminder S. Sachdev et al. INTERNATIONAL PSYCHOGERIATRICS
- The Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging: methodology and baseline characteristics of 1112 individuals recruited for a longitudinal study of Alzheimer's disease
- (2009) Kathryn A Ellis et al. INTERNATIONAL PSYCHOGERIATRICS
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