Data augmentation for medical imaging: A systematic literature review
Abstract Recent advances in Deep Learning have largely benefited from larger and more
diverse training sets. However, collecting large datasets for medical imaging is still a …
diverse training sets. However, collecting large datasets for medical imaging is still a …
Alzheimer's Disease Detection Using Deep Learning on Neuroimaging: A Systematic Review
Alzheimer's disease (AD) is a pressing global issue, demanding effective diagnostic
approaches. This systematic review surveys the recent literature (2018 onwards) to …
approaches. This systematic review surveys the recent literature (2018 onwards) to …
Lung nodules localization and report analysis from computerized tomography (CT) scan using a novel machine learning approach
A lung nodule is a tiny growth that develops in the lung. Non-cancerous nodules do not
spread to other sections of the body. Malignant nodules can spread rapidly. One of the …
spread to other sections of the body. Malignant nodules can spread rapidly. One of the …
A novel framework for classification of different Alzheimer's disease stages using CNN model
G Mohi ud din dar, A Bhagat, SI Ansarullah… - Electronics, 2023 - mdpi.com
Background: Alzheimer's, the predominant formof dementia, is a neurodegenerative brain
disorder with no known cure. With the lack of innovative findings to diagnose and treat …
disorder with no known cure. With the lack of innovative findings to diagnose and treat …
Development and validation of embedded device for electrocardiogram arrhythmia empowered with transfer learning
With the emergence of the Internet of Things (IoT), investigation of different diseases in
healthcare improved, and cloud computing helped to centralize the data and to access …
healthcare improved, and cloud computing helped to centralize the data and to access …
On disharmony in batch normalization and dropout methods for early categorization of Alzheimer's disease
Alzheimer's disease (AD) is a global health issue that predominantly affects older people. It
affects one's daily activities by modifying neural networks in the brain. AD is categorized by …
affects one's daily activities by modifying neural networks in the brain. AD is categorized by …
A novel expert system for the diagnosis and treatment of heart disease
The diagnosis of diseases in their early stages can assist us in preventing life-threatening
infections and caring for them better than in the last phase because prevention is better than …
infections and caring for them better than in the last phase because prevention is better than …
Automatic Analysis of MRI Images for Early Prediction of Alzheimer's Disease Stages Based on Hybrid Features of CNN and Handcrafted Features
A Khalid, EM Senan, K Al-Wagih, MM Ali Al-Azzam… - Diagnostics, 2023 - mdpi.com
Alzheimer's disease (AD) is considered one of the challenges facing health care in the
modern century; until now, there has been no effective treatment to cure it, but there are …
modern century; until now, there has been no effective treatment to cure it, but there are …
A review of the application of three-dimensional convolutional neural networks for the diagnosis of Alzheimer's disease using neuroimaging
X Xu, L Lin, S Sun, S Wu - Reviews in the Neurosciences, 2023 - degruyter.com
Alzheimer's disease (AD) is a degenerative disorder that leads to progressive, irreversible
cognitive decline. To obtain an accurate and timely diagnosis and detect AD at an early …
cognitive decline. To obtain an accurate and timely diagnosis and detect AD at an early …
Deep learning based computer aided diagnosis of Alzheimer's disease: a snapshot of last 5 years, gaps, and future directions
A Bhandarkar, P Naik, K Vakkund… - Artificial Intelligence …, 2024 - Springer
Alzheimer's disease affects around one in every nine persons among the elderly population.
Being a neurodegenerative disease, its cure has not been established till date and is …
Being a neurodegenerative disease, its cure has not been established till date and is …