Harnessing the power of machine learning in dementia informatics research: Issues, opportunities, and challenges

G Tsang, X Xie, SM Zhou - IEEE reviews in biomedical …, 2019 - ieeexplore.ieee.org
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 …

Harnessing the potential of machine learning and artificial intelligence for dementia research

JM Ranson, M Bucholc, D Lyall, D Newby… - Brain informatics, 2023 - Springer
Progress in dementia research has been limited, with substantial gaps in our knowledge of
targets for prevention, mechanisms for disease progression, and disease-modifying …

Neuroimaging and machine learning for dementia diagnosis: recent advancements and future prospects

MR Ahmed, Y Zhang, Z Feng, B Lo… - IEEE reviews in …, 2018 - ieeexplore.ieee.org
Dementia, a chronic and progressive cognitive declination of brain function caused by
disease or impairment, is becoming more prevalent due to the aging population. A major …

[HTML][HTML] Ten years of image analysis and machine learning competitions in dementia

EE Bron, S Klein, A Reinke, JM Papma, L Maier-Hein… - NeuroImage, 2022 - Elsevier
Abstract Machine learning methods exploiting multi-parametric biomarkers, especially
based on neuroimaging, have huge potential to improve early diagnosis of dementia and to …

Applications of artificial intelligence in dementia research

KKF Tsoi, P Jia, NM Dowling, JR Titiner… - Cambridge Prisms …, 2023 - cambridge.org
More than 50 million older people worldwide are suffering from dementia, and this number is
estimated to increase to 150 million by 2050. Greater caregiver burdens and financial …

An efficient way of identifying alzheimer's disease using deep learning techniques

K Gupta, N Jiwani, P Whig - Proceedings of Third Doctoral Symposium on …, 2022 - Springer
Alzheimer's disease has recently emerged as a big worry. This condition affects around 45
million people. Alzheimer's disease is a deteriorating brain illness through an unknown …

Multimodal deep learning for Alzheimer's disease dementia assessment

S Qiu, MI Miller, PS Joshi, JC Lee, C Xue, Y Ni… - Nature …, 2022 - nature.com
Worldwide, there are nearly 10 million new cases of dementia annually, of which
Alzheimer's disease (AD) is the most common. New measures are needed to improve the …

Artificial intelligence for dementia research methods optimization

M Bucholc, C James, AA Khleifat… - Alzheimer's & …, 2023 - Wiley Online Library
Artificial intelligence (AI) and machine learning (ML) approaches are increasingly being
used in dementia research. However, several methodological challenges exist that may limit …

Exploring deep transfer learning techniques for Alzheimer's dementia detection

Y Zhu, X Liang, JA Batsis, RM Roth - Frontiers in computer science, 2021 - frontiersin.org
Examination of speech datasets for detecting dementia, collected via various speech tasks,
has revealed links between speech and cognitive abilities. However, the speech dataset …

Develop a diagnostic tool for dementia using machine learning and non-imaging features

H Wang, L Sheng, S Xu, Y Jin, X Jin, S Qiao… - Frontiers in aging …, 2022 - frontiersin.org
Background Early identification of Alzheimer's disease or mild cognitive impairment can help
guide direct prevention and supportive treatments, improve outcomes, and reduce medical …