A systematic review on recent advancements in deep and machine learning based detection and classification of acute lymphoblastic leukemia
Automatic Leukemia or blood cancer detection is a challenging job and is very much
required in healthcare centers. It has a significant role in early diagnosis and treatment …
required in healthcare centers. It has a significant role in early diagnosis and treatment …
A systematic literature review on the significance of deep learning and machine learning in predicting Alzheimer's disease
Background Alzheimer's disease (AD) is the most prevalent cause of dementia,
characterized by a steady decline in mental, behavioral, and social abilities and impairs a …
characterized by a steady decline in mental, behavioral, and social abilities and impairs a …
A modified LeNet CNN for breast cancer diagnosis in ultrasound images
S Balasubramaniam, Y Velmurugan, D Jaganathan… - Diagnostics, 2023 - mdpi.com
Convolutional neural networks (CNNs) have been extensively utilized in medical image
processing to automatically extract meaningful features and classify various medical …
processing to automatically extract meaningful features and classify various medical …
A new strategy for the early detection of alzheimer disease stages using multifractal geometry analysis based on K-Nearest Neighbor algorithm
YM Elgammal, MA Zahran, MM Abdelsalam - Scientific reports, 2022 - nature.com
Alzheimer's Disease (AD) is considered one of the most diseases that much prevalent
among elderly people all over the world. AD is an incurable neurodegenerative disease …
among elderly people all over the world. AD is an incurable neurodegenerative disease …
A novel CNN architecture for accurate early detection and classification of Alzheimer's disease using MRI data
Alzheimer's disease (AD) is a debilitating neurodegenerative disorder that requires accurate
diagnosis for effective management and treatment. In this article, we propose an architecture …
diagnosis for effective management and treatment. In this article, we propose an architecture …
A review paper about deep learning for medical image analysis
B Sistaninejhad, H Rasi, P Nayeri - … and Mathematical Methods …, 2023 - Wiley Online Library
Medical imaging refers to the process of obtaining images of internal organs for therapeutic
purposes such as discovering or studying diseases. The primary objective of medical image …
purposes such as discovering or studying diseases. The primary objective of medical image …
Machine learning based healthcare system for investigating the association between depression and quality of life
New technological innovations are changing the future of healthcare system. Identification of
factors that are responsible for causing depression may lead to new experiments and …
factors that are responsible for causing depression may lead to new experiments and …
A novel machine learning based technique for classification of early-stage alzheimer's disease using brain images
Alzheimer's disease (AD) is a globally alarming neuro-degenerative abnormality for elderly
people. The earliest afflicted regions in AD are the brain tissues that form memory and other …
people. The earliest afflicted regions in AD are the brain tissues that form memory and other …
Structure focused neurodegeneration convolutional neural network for modelling and classification of Alzheimer's disease
S Odimayo, CC Olisah, K Mohammed - Scientific Reports, 2024 - nature.com
Abstract Alzheimer's disease (AD), the predominant form of dementia, is a growing global
challenge, emphasizing the urgent need for accurate and early diagnosis. Current clinical …
challenge, emphasizing the urgent need for accurate and early diagnosis. Current clinical …
Classification of Alzheimer disease using DenseNet-201 based on deep transfer learning technique
Alzheimer's disease (AD) is a brain illness that causes gradual memory loss. AD has no
treatment and cannot be cured, so early detection is critical. Various AD diagnosis …
treatment and cannot be cured, so early detection is critical. Various AD diagnosis …