Ensemble deep learning in bioinformatics
The remarkable flexibility and adaptability of ensemble methods and deep learning models
have led to the proliferation of their application in bioinformatics research. Traditionally …
have led to the proliferation of their application in bioinformatics research. Traditionally …
[HTML][HTML] Application of deep learning in breast cancer imaging
This review gives an overview of the current state of deep learning research in breast cancer
imaging. Breast imaging plays a major role in detecting breast cancer at an earlier stage, as …
imaging. Breast imaging plays a major role in detecting breast cancer at an earlier stage, as …
Magnetic resonance imaging-based brain tumor grades classification and grading via convolutional neural networks and genetic algorithms
AK Anaraki, M Ayati, F Kazemi - biocybernetics and biomedical engineering, 2019 - Elsevier
Gliomas are the most common type of primary brain tumors in adults and their early
detection is of great importance. In this paper, a method based on convolutional neural …
detection is of great importance. In this paper, a method based on convolutional neural …
Deep learning and medical diagnosis: A review of literature
M Bakator, D Radosav - Multimodal Technologies and Interaction, 2018 - mdpi.com
In this review the application of deep learning for medical diagnosis is addressed. A
thorough analysis of various scientific articles in the domain of deep neural networks …
thorough analysis of various scientific articles in the domain of deep neural networks …
Deep learning-based breast cancer classification through medical imaging modalities: state of the art and research challenges
Breast cancer is a common and fatal disease among women worldwide. Therefore, the early
and precise diagnosis of breast cancer plays a pivotal role to improve the prognosis of …
and precise diagnosis of breast cancer plays a pivotal role to improve the prognosis of …
Semantic segmentation of breast cancer images using DenseNet with proposed PSPNet
S Samudrala, CK Mohan - Multimedia Tools and Applications, 2024 - Springer
For early detection of cancer tumors, the semantic segmentation based technique is
proposed because the existing numerous methods fail while classifying due to accuracy and …
proposed because the existing numerous methods fail while classifying due to accuracy and …
Artificial intelligence for breast cancer analysis: Trends & directions
Breast cancer is one of the leading causes of death among women. Early detection of breast
cancer can significantly improve the lives of millions of women across the globe. Given …
cancer can significantly improve the lives of millions of women across the globe. Given …
Breast Cancer Prediction Empowered with Fine‐Tuning
In the world, in the past recent five years, breast cancer is diagnosed about 7.8 million
women's and making it the most widespread cancer, and it is the second major reason for …
women's and making it the most widespread cancer, and it is the second major reason for …
Ensemble of 3D densely connected convolutional network for diagnosis of mild cognitive impairment and Alzheimer's disease
Automatic diagnosis of Alzheimer's disease (AD) and mild cognition impairment (MCI) from
3D brain magnetic resonance (MR) images plays an important role in early treatment of …
3D brain magnetic resonance (MR) images plays an important role in early treatment of …
Macular OCT classification using a multi-scale convolutional neural network ensemble
Computer-aided diagnosis (CAD) of retinal pathologies is a current active area in medical
image analysis. Due to the increasing use of retinal optical coherence tomography (OCT) …
image analysis. Due to the increasing use of retinal optical coherence tomography (OCT) …