BreaST-Net: Multi-Class Classification of Breast Cancer from Histopathological Images Using Ensemble of Swin Transformers

Breast Cancer Classification from Ultrasound Images Using Probability-Based Optimal Deep Learning Feature Fusion

(2022) Kiran Jabeen et al.   SENSORS

Application of Deep Learning in Breast Cancer Imaging

(2022) Luuk Balkenende et al.   SEMINARS IN NUCLEAR MEDICINE

Multi-Class Classification of Breast Cancer Using 6B-Net with Deep Feature Fusion and Selection Method

(2022) Muhammad Junaid Umer et al.   Journal of Personalized Medicine

The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation

(2021) Davide Chicco et al.   BioData Mining

Breast mass classification with transfer learning based on scaling of deep representations

(2021) Michal Byra   Biomedical Signal Processing and Control

Automatic semantic segmentation of breast tumors in ultrasound images based on combining fuzzy logic and deep learning—A feasibility study

(2021) Samir M. Badawy et al.   PLoS One

Advantages and Challenges of Using Breast Biopsy Markers

(2021) Taghreed I Alshafeiy et al.   Journal of Breast Imaging

Breast cancer detection from histopathology images using modified residual neural networks

(2021) Varun Gupta et al.   Biocybernetics and Biomedical Engineering

Mammography Image-Based Diagnosis of Breast Cancer Using Machine Learning: A Pilot Study

(2021) Maha M. Alshammari et al.   SENSORS

SA-GAN: Stain Acclimation Generative Adversarial Network for Histopathology Image Analysis

(2021) Tasleem Kausar et al.   Applied Sciences-Basel

Cancer Cell Profiling Using Image Moments and Neural Networks with Model Agnostic Explainability: A Case Study of Breast Cancer Histopathological (BreakHis) Database

(2021) Dmitry Kaplun et al.   Mathematics

The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation

(2020) Davide Chicco et al.   BMC GENOMICS

Identification of Breast Malignancy by Marker-Controlled Watershed Transformation and Hybrid Feature Set for Healthcare

(2020) Tariq Sadad et al.   Applied Sciences-Basel

Breast Cancer Histopathology Image Classification Using an Ensemble of Deep Learning Models

(2020) Zabit Hameed et al.   SENSORS

Breast Cancer Image Classification: A Review

(2020) Pooja Pathak et al.   Current Medical Imaging Reviews

Breast cancer histopathological image classification using convolutional neural networks with small SE-ResNet module

(2019) Yun Jiang et al.   PLoS One

Breast Cancer Classification from Histopathological Images with Inception Recurrent Residual Convolutional Neural Network

(2019) Md Zahangir Alom et al.   JOURNAL OF DIGITAL IMAGING

Breast Cancer Detection and Diagnosis Using Mammographic Data: Systematic Review

(2019) Syed Jamal Safdar Gardezi et al.   JOURNAL OF MEDICAL INTERNET RESEARCH

Breast cancer histopathological image classification using a hybrid deep neural network

(2019) Rui Yan et al.   METHODS

Detecting and classifying lesions in mammograms with Deep Learning

(2018) Dezső Ribli et al.   Scientific Reports

Classification of Breast Cancer Based on Histology Images Using Convolutional Neural Networks

(2018) Dalal Bardou et al.   IEEE Access

Comparative Accuracy of Mammography and Ultrasound in Women with Breast Symptoms According to Age and Breast Density

(2018) Emine Devolli-Disha et al.   Bosnian Journal of Basic Medical Sciences

A guide to deep learning in healthcare

(2018) Andre Esteva et al.   NATURE MEDICINE

Breast Cancer Multi-classification from Histopathological Images with Structured Deep Learning Model

(2017) Zhongyi Han et al.   Scientific Reports

A Dataset for Breast Cancer Histopathological Image Classification

(2016) Fabio A. Spanhol et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Estrogen Receptor Status and the Future Burden of Invasive and In Situ Breast Cancers in the United States

(2015) Philip S. Rosenberg et al.   JNCI-Journal of the National Cancer Institute

Estrogen Receptor Status and the Future Burden of Invasive and In Situ Breast Cancers in the United States

(2015) Philip S. Rosenberg et al.   JNCI-Journal of the National Cancer Institute

Breast Cancer Histopathology Image Analysis: A Review

(2014) Mitko Veta et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

A Comparison of Mammography and Ultrasound in Women with Breast Disease: A Receiver Operating Characteristic Analysis

(2012) Xuexiang Ying et al.   Breast Journal