Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slides, BCNB Dataset
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Updated
May 8, 2023 - Python
Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slides, BCNB Dataset
Code for Paper: Multi Scale Curriculum CNN for Context-Aware Breast MRI Malignancy Classification
1st place solution to the Breast Cancer Classification Task of HeLP Challenge 2019.
Breast Cancer Image Classification On WSI With Spatial Correlations https://teacher.bupt.edu.cn/zhuchuang/en/index.htm
Using the Knn algorithm, it detects whether the tumor is benign or malignant in people diagnosed with breast cancer.
Memory-aware curriculum federated learning for breast cancer classification. Computer Methods and Programs in Biomedicine.
A text-based computational framework for patient -specific modeling for classification of cancers. iScience (2022).
Streamlit application to classify cancer as malignant or benign.
SWSSL - Sliding window-based self-supervised learning for anomaly detection in high-resolution images (IEEE Trans. on Medical Imaging 2023)
Harnessing Deep Learning for Enhanced Mammogram Analysis
logistic regression from scratch using python to solve binary classification problem using breast cancer dataset from scikit-learn. A complete breakdown of logistic regression algorithm.
In this repository, I implemented the deep learning classifier introduced in the paper "Deep Learning to Improve Breast Cancer Detection on Screening Mammography" using PyTorch.
The aim is to categorize and accurately identify the types and subtypes of breast cancer
HRadNet: A Hierarchical Radiomics-based Network for Multicenter Breast Cancer Molecular Subtypes Prediction, TMI
Small project to accurately predict nature of a tumour (benign/malignant) using the UCI Wisconsin breast cancer dataset (https://www.kaggle.com/uciml/breast-cancer-wisconsin-data)
Interpretable breast cancer classification using convolutional neural networks on mammographic images
Scikit-Learn Supervised Machine Learning for Breast Cancer Binary Classification
Breast Cancer Classifier
The aim is to categorise and accurately identify the types and subtypes of breast cancer
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