Transfer learning techniques for medical image analysis: A review
Medical imaging is a useful tool for disease detection and diagnostic imaging technology
has enabled early diagnosis of medical conditions. Manual image analysis methods are …
has enabled early diagnosis of medical conditions. Manual image analysis methods are …
Machine learning techniques for the diagnosis of Alzheimer's disease: A review
Alzheimer's disease is an incurable neurodegenerative disease primarily affecting the
elderly population. Efficient automated techniques are needed for early diagnosis of …
elderly population. Efficient automated techniques are needed for early diagnosis of …
Transfer learning in magnetic resonance brain imaging: A systematic review
(1) Background: Transfer learning refers to machine learning techniques that focus on
acquiring knowledge from related tasks to improve generalization in the tasks of interest. In …
acquiring knowledge from related tasks to improve generalization in the tasks of interest. In …
[HTML][HTML] Advancements in computer-assisted diagnosis of Alzheimer's disease: A comprehensive survey of neuroimaging methods and AI techniques for early …
Alzheimer's Disease (AD) is a brain disorder that causes the brain to shrink and eventually
causes brain cells to die. This neurological condition progressively hampers cognitive and …
causes brain cells to die. This neurological condition progressively hampers cognitive and …
Transfer learning approaches for neuroimaging analysis: a sco** review
Deep learning algorithms have been moderately successful in diagnoses of diseases by
analyzing medical images especially through neuroimaging that is rich in annotated data …
analyzing medical images especially through neuroimaging that is rich in annotated data …
Brain asymmetry detection and machine learning classification for diagnosis of early dementia
NJ Herzog, GD Magoulas - Sensors, 2021 - mdpi.com
Early identification of degenerative processes in the human brain is considered essential for
providing proper care and treatment. This may involve detecting structural and functional …
providing proper care and treatment. This may involve detecting structural and functional …
Decgan: decoupling generative adversarial network for detecting abnormal neural circuits in Alzheimer's disease
One of the main reasons for Alzheimer's disease (AD) is the disorder of some neural circuits.
Existing methods for AD prediction have achieved great success, however, detecting …
Existing methods for AD prediction have achieved great success, however, detecting …
Improving the classification of alzheimer's disease using hybrid gene selection pipeline and deep learning
Alzheimer's is a progressive, irreversible, neurodegenerative brain disease. Even with
prominent symptoms, it takes years to notice, decode, and reveal Alzheimer's. However …
prominent symptoms, it takes years to notice, decode, and reveal Alzheimer's. However …
Biceph-Net: A robust and lightweight framework for the diagnosis of Alzheimer's disease using 2D-MRI scans and deep similarity learning
AH Rashid, A Gupta, J Gupta… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Alzheimer's Disease (AD) is a neurodegenerative disease that is one of the significant
causes of death in the elderly population. Many deep learning techniques have been …
causes of death in the elderly population. Many deep learning techniques have been …
A novel cascade machine learning pipeline for Alzheimer's disease identification and prediction
K Zhou, S Piao, X Liu, X Luo, H Chen… - Frontiers in Aging …, 2023 - frontiersin.org
Introduction Alzheimer's disease (AD) is a progressive and irreversible brain degenerative
disorder early. Among all diagnostic strategies, hippocampal atrophy is considered a …
disorder early. Among all diagnostic strategies, hippocampal atrophy is considered a …