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Domain adaptation for medical image analysis: a survey
Machine learning techniques used in computer-aided medical image analysis usually suffer
from the domain shift problem caused by different distributions between source/reference …
from the domain shift problem caused by different distributions between source/reference …
Data-driven modelling of neurodegenerative disease progression: thinking outside the black box
Data-driven disease progression models are an emerging set of computational tools that
reconstruct disease timelines for long-term chronic diseases, providing unique insights into …
reconstruct disease timelines for long-term chronic diseases, providing unique insights into …
Deep learning approach for early detection of Alzheimer's disease
Alzheimer's disease (AD) is a chronic, irreversible brain disorder, no effective cure for it till
now. However, available medicines can delay its progress. Therefore, the early detection of …
now. However, available medicines can delay its progress. Therefore, the early detection of …
Alzheimer disease detection empowered with transfer learning
Alzheimer's disease is a severe neuron disease that damages brain cells which leads to
permanent loss of memory also called dementia. Many people die due to this disease every …
permanent loss of memory also called dementia. Many people die due to this disease every …
Deep learning to detect Alzheimer's disease from neuroimaging: A systematic literature review
Alzheimer's Disease (AD) is one of the leading causes of death in developed countries.
From a research point of view, impressive results have been reported using computer-aided …
From a research point of view, impressive results have been reported using computer-aided …
A systematic survey of computer-aided diagnosis in medicine: Past and present developments
J Yanase, E Triantaphyllou - Expert Systems with Applications, 2019 - Elsevier
Computer-aided diagnosis (CAD) in medicine is the result of a large amount of effort
expended in the interface of medicine and computer science. As some CAD systems in …
expended in the interface of medicine and computer science. As some CAD systems in …
Convolutional neural network based Alzheimer's disease classification from magnetic resonance brain images
Alzheimer's disease, the most common form of dementia is a neurodegenerative brain order
that has currently no cure for it. Hence, early diagnosis of such disease using computer …
that has currently no cure for it. Hence, early diagnosis of such disease using computer …
Prediction of Alzheimer's progression based on multimodal deep-learning-based fusion and visual explainability of time-series data
Alzheimer's disease (AD) is a neurological illness that causes cognitive impairment and has
no known treatment. The premise for delivering timely therapy is the early diagnosis of AD …
no known treatment. The premise for delivering timely therapy is the early diagnosis of AD …
A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages
Neuroimaging has made it possible to measure pathological brain changes associated with
Alzheimer's disease (AD) in vivo. Over the past decade, these measures have been …
Alzheimer's disease (AD) in vivo. Over the past decade, these measures have been …
Artificial intelligence in neurodegenerative diseases: A review of available tools with a focus on machine learning techniques
Neurodegenerative diseases have shown an increasing incidence in the older population in
recent years. A significant amount of research has been conducted to characterize these …
recent years. A significant amount of research has been conducted to characterize these …