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 …
Machine learning methods for cancer classification using gene expression data: A review
F Alharbi, A Vakanski - Bioengineering, 2023 - mdpi.com
Cancer is a term that denotes a group of diseases caused by the abnormal growth of cells
that can spread in different parts of the body. According to the World Health Organization …
that can spread in different parts of the body. According to the World Health Organization …
BC2NetRF: Breast Cancer Classification from Mammogram Images Using Enhanced Deep Learning Features and Equilibrium-Jaya Controlled Regula Falsi-Based …
One of the most frequent cancers in women is breast cancer, and in the year 2022,
approximately 287,850 new cases have been diagnosed. From them, 43,250 women died …
approximately 287,850 new cases have been diagnosed. From them, 43,250 women died …
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 …
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 …
A self-learning deep neural network for classification of breast histopathological images
The most effective and feasible method for treating cancer is early diagnosis of breast
cancer. An appropriate software tool, known as computer-aided diagnosis, helps doctors …
cancer. An appropriate software tool, known as computer-aided diagnosis, helps doctors …
A novel approach for breast cancer detection using optimized ensemble learning framework and XAI
Breast cancer (BC) is a common and highly lethal ailment. It stands as the second leading
contributor to cancer-related deaths in women worldwide. The timely identification of this …
contributor to cancer-related deaths in women worldwide. The timely identification of this …
Towards artificial intelligence applications in next generation cytopathology
E Giarnieri, S Scardapane - Biomedicines, 2023 - mdpi.com
Over the last 20 years we have seen an increase in techniques in the field of computational
pathology and machine learning, improving our ability to analyze and interpret imaging …
pathology and machine learning, improving our ability to analyze and interpret imaging …
Compatible-domain transfer learning for breast cancer classification with limited annotated data
Microscopic analysis of breast cancer images is the primary task in diagnosing cancer
malignancy. Recent attempts to automate this task have employed deep learning models …
malignancy. Recent attempts to automate this task have employed deep learning models …
Breast Cancer Classification from Mammogram Images Using Extreme Learning Machine‐Based DenseNet121 Model
Breast cancer is characterized by abnormal discontinuities in the lining cells of a woman's
milk duct. Large numbers of women die from breast cancer as a result of developing …
milk duct. Large numbers of women die from breast cancer as a result of developing …