A brief survey on breast cancer diagnostic with deep learning schemes using multi-image modalities
Patients with breast cancer are prone to serious health-related complications with higher
mortality. The primary reason might be a misinterpretation of radiologists in recognizing …
mortality. The primary reason might be a misinterpretation of radiologists in recognizing …
An integrated framework for breast mass classification and diagnosis using stacked ensemble of residual neural networks
A computer-aided diagnosis (CAD) system requires automated stages of tumor detection,
segmentation, and classification that are integrated sequentially into one framework to assist …
segmentation, and classification that are integrated sequentially into one framework to assist …
Optimised CNN in conjunction with efficient pooling strategy for the multi‐classification of breast cancer
Tissue analysis using histopathological images is the most prevailing as well as a
challenging task in the treatment of cancer. The clinical assessment of tissues becomes very …
challenging task in the treatment of cancer. The clinical assessment of tissues becomes very …
Machine learning-based approach for early diagnosis of breast cancer using biomarkers and gene expression profiles
Breast cancer is a heterogeneous disease and the most frequent malignancy in women
globally each year. Emerging applications of gene expression profiles are important to …
globally each year. Emerging applications of gene expression profiles are important to …
A fuzzy based high-resolution multi-view deep CNN for breast cancer diagnosis through SVM classifier on visual analysis
Breast cancer should be diagnosed as early as possible. A new approach of the diagnosis
using deep learning for breast cancer and the particular process using segmentation …
using deep learning for breast cancer and the particular process using segmentation …
DF-dRVFL: A novel deep feature based classifier for breast mass classification
Amongst all types of cancer, breast cancer has become one of the most common cancers in
the UK threatening millions of people's health. Early detection of breast cancer plays a key …
the UK threatening millions of people's health. Early detection of breast cancer plays a key …
Framework for classification of cancer gene expression data using Bayesian hyper-parameter optimization
Computational classification of cancers is an important research problem. Gene expression
data has 1000s of features, very few samples, and a class imbalance problem. In this paper …
data has 1000s of features, very few samples, and a class imbalance problem. In this paper …
[PDF][PDF] A logistic regression based hybrid model for breast cancer classification
Data mining techniques are being used for breast cancer classification and good
performance accuracy has been obtained while using the techniques individually or as …
performance accuracy has been obtained while using the techniques individually or as …
An improved Tabu search algorithm for multi-robot hybrid disassembly line balancing problems
In recent years, the progress in the global industrialization process and the continuous
advances in science and technology have brought great improvement to people's living …
advances in science and technology have brought great improvement to people's living …
Diagnosing malaria from some symptoms: a machine learning approach and public health implications
Malaria is a leading cause of death in Nigeria and remains a public health concern because
of the increasing resistance of the disease to antimalarial drugs. Pregnant women and …
of the increasing resistance of the disease to antimalarial drugs. Pregnant women and …