Emerging applications of machine learning in genomic medicine and healthcare
The integration of artificial intelligence technologies has propelled the progress of clinical
and genomic medicine in recent years. The significant increase in computing power has …
and genomic medicine in recent years. The significant increase in computing power has …
[HTML][HTML] A survey of convolutional neural network in breast cancer
Aims A large number of clinical trials have proved that if breast cancer is diagnosed at an
early stage, it could give patients more treatment options and improve the treatment effect …
early stage, it could give patients more treatment options and improve the treatment effect …
[HTML][HTML] Medical internet-of-things based breast cancer diagnosis using hyperparameter-optimized neural networks
In today's healthcare setting, the accurate and timely diagnosis of breast cancer is critical for
recovery and treatment in the early stages. In recent years, the Internet of Things (IoT) has …
recovery and treatment in the early stages. In recent years, the Internet of Things (IoT) has …
[HTML][HTML] Breast cancer detection using mammogram images with improved multi-fractal dimension approach and feature fusion
DA Zebari, DA Ibrahim, DQ Zeebaree… - Applied Sciences, 2021 - mdpi.com
Breast cancer detection using mammogram images at an early stage is an important step in
disease diagnostics. We propose a new method for the classification of benign or malignant …
disease diagnostics. We propose a new method for the classification of benign or malignant …
Automated breast cancer detection in mammography using ensemble classifier and feature weighting algorithms
Breast cancer exhibits one of the highest incidence and mortality rates among all cancers
affecting women. The early detection of breast cancer reduces mortality and is crucial for …
affecting women. The early detection of breast cancer reduces mortality and is crucial for …
[HTML][HTML] A multi-agent deep reinforcement learning approach for enhancement of COVID-19 CT image segmentation
Currently, most mask extraction techniques are based on convolutional neural networks
(CNNs). However, there are still numerous problems that mask extraction techniques need …
(CNNs). However, there are still numerous problems that mask extraction techniques need …
Classification of breast cancer histopathological images using DenseNet and transfer learning
Breast cancer is one of the most common invading cancers in women. Analyzing breast
cancer is nontrivial and may lead to disagreements among experts. Although deep learning …
cancer is nontrivial and may lead to disagreements among experts. Although deep learning …
A deep learning approach for automatic detection, segmentation and classification of breast lesions from thermal images
Purpose This study investigates implementation of deep learning (DL) approaches to breast
tumor recognition based on thermal images. We propose to utilize Mask R-CNN technique …
tumor recognition based on thermal images. We propose to utilize Mask R-CNN technique …
[HTML][HTML] Breast cancer screening based on supervised learning and multi-criteria decision-making
On average, breast cancer kills one woman per minute. However, there are more reasons
for optimism than ever before. When diagnosed early, patients with breast cancer have a …
for optimism than ever before. When diagnosed early, patients with breast cancer have a …
An efficient deep learning scheme to detect breast cancer using mammogram and ultrasound breast images
Breast cancer is the second major reason of death among women around the world. Early
and accurate breast cancer detection is important for proper treatment planning to save a …
and accurate breast cancer detection is important for proper treatment planning to save a …