[HTML][HTML] A review and comparative study of cancer detection using machine learning: SBERT and SimCSE application
M Mokoatle, V Marivate, D Mapiye, R Bornman… - BMC …, 2023 - Springer
Background Using visual, biological, and electronic health records data as the sole input
source, pretrained convolutional neural networks and conventional machine learning …
source, pretrained convolutional neural networks and conventional machine learning …
Cancer detection and segmentation using machine learning and deep learning techniques: A review
HM Rai - Multimedia Tools and Applications, 2024 - Springer
Cancer is the most fatal diseases in the world which has highest mortality rate as compared
to other type's human diseases. The most common and dangerous types of cancers are lung …
to other type's human diseases. The most common and dangerous types of cancers are lung …
[HTML][HTML] A secure internet of medical things framework for breast cancer detection in sustainable smart cities
Computational intelligence (CI) and artificial intelligence (AI) have incredible roles to play in
the development of smart and sustainable healthcare systems by facilitating the integration …
the development of smart and sustainable healthcare systems by facilitating the integration …
[HTML][HTML] The stratified K-folds cross-validation and class-balancing methods with high-performance ensemble classifiers for breast cancer classification
Breast cancer is one of the most common causes of death among women, and early
diagnosis is vital for reducing the fatality rate. This study evaluates the most widely used …
diagnosis is vital for reducing the fatality rate. This study evaluates the most widely used …
Abnormality classification and localization using dual-branch whole-region-based CNN model with histopathological images
The task of classification and localization with detecting abnormalities in medical images is
considered very challenging. Computer-aided systems have been widely employed to …
considered very challenging. Computer-aided systems have been widely employed to …
[HTML][HTML] Enhanced Pre-Trained Xception Model Transfer Learned for Breast Cancer Detection
Early detection and timely breast cancer treatment improve survival rates and patients'
quality of life. Hence, many computer-assisted techniques based on artificial intelligence are …
quality of life. Hence, many computer-assisted techniques based on artificial intelligence are …
[HTML][HTML] A blockchain-enabled internet of medical things system for breast cancer detection in healthcare
S Chaudhury, K Sau - Healthcare Analytics, 2023 - Elsevier
Intelligent and sustainable healthcare systems can considerably benefit from applying
Computational Intelligence (CI) and Artificial Intelligence (AI). These technological …
Computational Intelligence (CI) and Artificial Intelligence (AI). These technological …
[HTML][HTML] BRMI-Net: Deep Learning Features and Flower Pollination-Controlled Regula Falsi-Based Feature Selection Framework for Breast Cancer Recognition in …
The early detection of breast cancer using mammogram images is critical for lowering
women's mortality rates and allowing for proper treatment. Deep learning techniques are …
women's mortality rates and allowing for proper treatment. Deep learning techniques are …
A comprehensive analysis of recent advancements in cancer detection using machine learning and deep learning models for improved diagnostics
Purpose There are millions of people who lose their life due to several types of fatal
diseases. Cancer is one of the most fatal diseases which may be due to obesity, alcohol …
diseases. Cancer is one of the most fatal diseases which may be due to obesity, alcohol …
Evolution of LiverNet 2. x: Architectures for automated liver cancer grade classification from H&E stained liver histopathological images
AK Chanchal, S Lal, D Barnwal, P Sinha… - Multimedia Tools and …, 2024 - Springer
Recently, the automation of disease identification has been quite popular in the field of
medical diagnosis. The rise of Convolutional Neural Networks (CNNs) for training and …
medical diagnosis. The rise of Convolutional Neural Networks (CNNs) for training and …