A comprehensive review on breast cancer detection, classification and segmentation using deep learning
The incidence and mortality rate of Breast Cancer (BC) are global problems for women, with
over 2.1 million new diagnoses each year worldwide. There is no age range, race, or …
over 2.1 million new diagnoses each year worldwide. There is no age range, race, or …
Deep learning for medical image-based cancer diagnosis
Simple Summary Deep learning has succeeded greatly in medical image-based cancer
diagnosis. To help readers better understand the current research status and ideas, this …
diagnosis. To help readers better understand the current research status and ideas, this …
Multi-modal brain tumor detection using deep neural network and multiclass SVM
S Maqsood, R Damaševičius, R Maskeliūnas - Medicina, 2022 - mdpi.com
Background and Objectives: Clinical diagnosis has become very significant in today's health
system. The most serious disease and the leading cause of mortality globally is brain cancer …
system. The most serious disease and the leading cause of mortality globally is brain cancer …
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 …
Classification and diagnostic prediction of breast cancer metastasis on clinical data using machine learning algorithms
M Botlagunta, MD Botlagunta, MB Myneni… - Scientific Reports, 2023 - nature.com
Abstract Metastatic Breast Cancer (MBC) is one of the primary causes of cancer-related
deaths in women. Despite several limitations, histopathological information about the …
deaths in women. Despite several limitations, histopathological information about the …
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 …
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 …
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 …
Mammography and ultrasound based dual modality classification of breast cancer using a hybrid deep learning approach
Traditional methods of diagnosing breast cancer (BC) suffer from human errors, are less
accurate, and consume time. A computer-aided detection (CAD) system can overcome the …
accurate, and consume time. A computer-aided detection (CAD) system can overcome the …
Efficient breast cancer mammograms diagnosis using three deep neural networks and term variance
AS Elkorany, ZF Elsharkawy - Scientific Reports, 2023 - nature.com
Breast cancer (BC) is spreading more and more every day. Therefore, a patient's life can be
saved by its early discovery. Mammography is frequently used to diagnose BC. The …
saved by its early discovery. Mammography is frequently used to diagnose BC. The …