A study of CNN and transfer learning in medical imaging: Advantages, challenges, future scope
This paper presents a comprehensive study of Convolutional Neural Networks (CNN) and
transfer learning in the context of medical imaging. Medical imaging plays a critical role in …
transfer learning in the context of medical imaging. Medical imaging plays a critical role in …
Machine learning-based lung and colon cancer detection using deep feature extraction and ensemble learning
Cancer is a fatal disease caused by a combination of genetic diseases and a variety of
biochemical abnormalities. Lung and colon cancer have emerged as two of the leading …
biochemical abnormalities. Lung and colon cancer have emerged as two of the leading …
An efficient deep learning approach for colon cancer detection
Colon cancer is the second most common cause of cancer death in women and the third
most common cause of cancer death in men. Therefore, early detection of this cancer can …
most common cause of cancer death in men. Therefore, early detection of this cancer can …
Performance analysis of seven Convolutional Neural Networks (CNNs) with transfer learning for Invasive Ductal Carcinoma (IDC) grading in breast histopathological …
Abstract Computer-aided Invasive Ductal Carcinoma (IDC) grading classification systems
based on deep learning have shown that deep learning may achieve reliable accuracy in …
based on deep learning have shown that deep learning may achieve reliable accuracy in …
An explainable deep learning model to prediction dental caries using panoramic radiograph images
Dental caries is the most frequent dental health issue in the general population. Dental
caries can result in extreme pain or infections, lowering people's quality of life. Applying …
caries can result in extreme pain or infections, lowering people's quality of life. Applying …
A convolution neural network with multi-level convolutional and attention learning for classification of cancer grades and tissue structures in colon histopathological …
A clinically comparable Convolutional Neural Network framework-based technique for
performing automated classification of cancer grades and tissue structures in hematoxylin …
performing automated classification of cancer grades and tissue structures in hematoxylin …
COVID-19 detection on chest X-ray images with the proposed model using artificial intelligence and classifiers
Abstract Coronavirus disease-2019 (COVID-19) is a serious infectious disease that is
spreading rapidly all over the world. Scientists are looking for alternative diagnostic methods …
spreading rapidly all over the world. Scientists are looking for alternative diagnostic methods …
Multi-feature fusion and improved BO and IGWO metaheuristics based models for automatically diagnosing the sleep disorders from sleep sounds
A night of regular and quality sleep is vital in human life. Sleep quality has a great impact on
the daily life of people and those around them. Sounds such as snoring reduce not only the …
the daily life of people and those around them. Sounds such as snoring reduce not only the …
Ensemble-based multi-tissue classification approach of colorectal cancer histology images using a novel hybrid deep learning framework
M Khazaee Fadafen, K Rezaee - Scientific Reports, 2023 - nature.com
Colorectal cancer (CRC) is the second leading cause of cancer death in the world, so digital
pathology is essential for assessing prognosis. Due to the increasing resolution and quantity …
pathology is essential for assessing prognosis. Due to the increasing resolution and quantity …
What can machine vision do for lymphatic histopathology image analysis: a comprehensive review
Over the past 10 years, machine vision (MV) algorithms for image analysis have been
developing rapidly with computing power. At the same time, histopathological slices can be …
developing rapidly with computing power. At the same time, histopathological slices can be …