Machine learning techniques for diagnosis of alzheimer disease, mild cognitive disorder, and other types of dementia
Alzheimer's disease (AD) is one of the most common form of dementia which mostly affects
elderly people. AD identification in early stages is a difficult task in medical practice and …
elderly people. AD identification in early stages is a difficult task in medical practice and …
Machine learning and deep learning approaches for brain disease diagnosis: principles and recent advances
Brain is the controlling center of our body. With the advent of time, newer and newer brain
diseases are being discovered. Thus, because of the variability of brain diseases, existing …
diseases are being discovered. Thus, because of the variability of brain diseases, existing …
[HTML][HTML] A review of the application of deep learning in the detection of Alzheimer's disease
S Gao, D Lima - International Journal of Cognitive Computing in …, 2022 - Elsevier
Alzheimer's disease (AD) is the most common chronic disease in the elderly, with a high
incidence rate. In recent years, deep learning has become popular in the field of medical …
incidence rate. In recent years, deep learning has become popular in the field of medical …
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 …
Computational modeling of dementia prediction using deep neural network: analysis on OASIS dataset
Alzheimer is a progressive disease and it is the most prevalent neurodegenerative disorder.
It is believed that the people with mild cognitive impairment are at high risk of developing …
It is believed that the people with mild cognitive impairment are at high risk of developing …
A comprehensive review of machine learning algorithms and their application in geriatric medicine: present and future
RJ Woodman, AA Mangoni - Aging Clinical and Experimental Research, 2023 - Springer
The increasing access to health data worldwide is driving a resurgence in machine learning
research, including data-hungry deep learning algorithms. More computationally efficient …
research, including data-hungry deep learning algorithms. More computationally efficient …
Eeg-based alzheimer's disease recognition using robust-pca and lstm recurrent neural network
M Alessandrini, G Biagetti, P Crippa, L Falaschetti… - Sensors, 2022 - mdpi.com
The use of electroencephalography (EEG) has recently grown as a means to diagnose
neurodegenerative pathologies such as Alzheimer's disease (AD). AD recognition can …
neurodegenerative pathologies such as Alzheimer's disease (AD). AD recognition can …
A systematic review on machine learning and deep learning techniques in the effective diagnosis of Alzheimer's disease
AD Arya, SS Verma, P Chakarabarti, T Chakrabarti… - Brain Informatics, 2023 - Springer
Alzheimer's disease (AD) is a brain-related disease in which the condition of the patient gets
worse with time. AD is not a curable disease by any medication. It is impossible to halt the …
worse with time. AD is not a curable disease by any medication. It is impossible to halt the …
Automatic detection of Alzheimer's disease using deep learning models and neuro-imaging: current trends and future perspectives
T Illakiya, R Karthik - Neuroinformatics, 2023 - Springer
Deep learning algorithms have a huge influence on tackling research issues in the field of
medical image processing. It acts as a vital aid for the radiologists in producing accurate …
medical image processing. It acts as a vital aid for the radiologists in producing accurate …
A survey of deep learning for alzheimer's disease
Alzheimer's and related diseases are significant health issues of this era. The
interdisciplinary use of deep learning in this field has shown great promise and gathered …
interdisciplinary use of deep learning in this field has shown great promise and gathered …