Breast cancer detection using deep learning: Datasets, methods, and challenges ahead
Breast Cancer (BC) is the most commonly diagnosed cancer and second leading cause of
mortality among women. About 1 in 8 US women (about 13%) will develop invasive BC …
mortality among women. About 1 in 8 US women (about 13%) will develop invasive BC …
A review on recent developments in cancer detection using Machine Learning and Deep Learning models
Cancer is a fatal illness frequently caused by a variety of obsessive changes and genetic
disorders. Cancer cells knowing as abnormal cells can grow in any part of the human body …
disorders. Cancer cells knowing as abnormal cells can grow in any part of the human body …
Ensemble deep learning and internet of things‐based automated COVID‐19 diagnosis framework
AS Kini, AN Gopal Reddy, M Kaur… - Contrast Media & …, 2022 - Wiley Online Library
Coronavirus disease (COVID‐19) is a viral infection caused by SARS‐CoV‐2. The
modalities such as computed tomography (CT) have been successfully utilized for the early …
modalities such as computed tomography (CT) have been successfully utilized for the early …
MobileNet-SVM: A lightweight deep transfer learning model to diagnose BCH scans for IoMT-based imaging sensors
RO Ogundokun, S Misra, AO Akinrotimi, H Ogul - Sensors, 2023 - mdpi.com
Many individuals worldwide pass away as a result of inadequate procedures for prompt
illness identification and subsequent treatment. A valuable life can be saved or at least …
illness identification and subsequent treatment. A valuable life can be saved or at least …
Breast cancer classification through meta-learning ensemble technique using convolution neural networks
This study aims to develop an efficient and accurate breast cancer classification model using
meta-learning approaches and multiple convolutional neural networks. This Breast …
meta-learning approaches and multiple convolutional neural networks. This Breast …
Temporal feature aggregation with attention for insider threat detection from activity logs
P Pal, P Chattopadhyay, M Swarnkar - Expert Systems with Applications, 2023 - Elsevier
Nowadays, insider attacks are emerging as one of the top cybersecurity threats. However,
the detection of insider threats is a more arduous task for many reasons. A significant cause …
the detection of insider threats is a more arduous task for many reasons. A significant cause …
Classifying breast cancer using transfer learning models based on histopathological images
Deep learning algorithms are designed to learn from the data, where these require large
amount of training dataset for accurate prediction. Recent studies have depicted that transfer …
amount of training dataset for accurate prediction. Recent studies have depicted that transfer …
A review on computational methods for breast cancer detection in ultrasound images using multi-image modalities
S Sushanki, AK Bhandari, AK Singh - Archives of Computational Methods …, 2024 - Springer
Breast cancer is a kind of cancer that develops and propagates from tissues of the breast
and slowly transcends the whole body, this type of tumor is found in both sexes. Early …
and slowly transcends the whole body, this type of tumor is found in both sexes. Early …
Improved classification of colorectal polyps on histopathological images with ensemble learning and stain normalization
Abstract Background and Objective: Early detection of colon adenomatous polyps is critically
important because correct detection of it significantly reduces the potential of developing …
important because correct detection of it significantly reduces the potential of developing …
CNN-Wavelet scattering textural feature fusion for classifying breast tissue in mammograms
Visual interpretation from radiologists employs computer-aided diagnosis (CAD) to make
clinical diagnoses by analyzing breast tissue images and assessing their texture. Aside from …
clinical diagnoses by analyzing breast tissue images and assessing their texture. Aside from …