On the analyses of medical images using traditional machine learning techniques and convolutional neural networks
Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
ResNet-32 and FastAI for diagnoses of ductal carcinoma from 2D tissue slides
Carcinoma is a primary source of morbidity in women globally, with metastatic disease
accounting for most deaths. Its early discovery and diagnosis may significantly increase the …
accounting for most deaths. Its early discovery and diagnosis may significantly increase the …
DeepBreastCancerNet: A novel deep learning model for breast cancer detection using ultrasound images
Breast cancer causes hundreds of women's deaths each year. The manual detection of
breast cancer is time-consuming, complicated, and prone to inaccuracy. For Breast Cancer …
breast cancer is time-consuming, complicated, and prone to inaccuracy. For Breast Cancer …
An Efficient Optimization System for Early Breast Cancer Diagnosis based on Internet of Medical Things and Deep Learning
Improving patient outcomes and treatment efficacy requires effective early detection of
breast cancer. Recently, medical diagnostics has been transformed by merging the Internet …
breast cancer. Recently, medical diagnostics has been transformed by merging the Internet …
Machine and deep learning applications to mouse dynamics for continuous user authentication
Static authentication methods, like passwords, grow increasingly weak with advancements
in technology and attack strategies. Continuous authentication has been proposed as a …
in technology and attack strategies. Continuous authentication has been proposed as a …
MobileNet-SVM: A lightweight deep transfer learning model to diagnose BCH scans for IoMT-based imaging sensors
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 …
Selecting the optimal transfer learning model for precise breast cancer diagnosis utilizing pre-trained deep learning models and histopathology images
Abstract Background Every year, around 1.5 million women worldwide receive a breast
cancer diagnosis, which is why the mortality rate for women is rising. Scientists have …
cancer diagnosis, which is why the mortality rate for women is rising. Scientists have …
Classification of breast cancer using a manta-ray foraging optimized transfer learning framework
Due to its high prevalence and wide dissemination, breast cancer is a particularly
dangerous disease. Breast cancer survival chances can be improved by early detection and …
dangerous disease. Breast cancer survival chances can be improved by early detection and …
The roles of cloud-based systems on the cancer-related studies: a systematic literature review
B Xu, F Zhou - IEEE Access, 2022 - ieeexplore.ieee.org
The advances in wireless-based technologies and intelligent diagnostics and forecasting
such as cloud computing have significantly affected our lifestyle, observed in many fields …
such as cloud computing have significantly affected our lifestyle, observed in many fields …
Analyzing histological images using hybrid techniques for early detection of multi-class breast Cancer based on Fusion features of CNN and Handcrafted
Breast cancer is the second most common type of cancer among women, and it can threaten
women's lives if it is not diagnosed early. There are many methods for detecting breast …
women's lives if it is not diagnosed early. There are many methods for detecting breast …