breast_cancer_classifier and Deep-Learning-Approaches-for-Enhanced-Breast-Cancer-Detection

Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 0/25
Adoption 5/25
Maturity 16/25
Community 15/25
Stars: 886
Forks: 277
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: AGPL-3.0
Stars: 12
Forks: 4
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About breast_cancer_classifier

nyukat/breast_cancer_classifier

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening

This project helps radiologists and medical researchers evaluate breast cancer risk from mammography screenings. You input a set of four standard-view mammogram images (and optionally, heatmaps if you have them) and it outputs predictions for the probability of benign and malignant findings for each breast. This is designed for professionals involved in breast cancer screening and research who use mammogram images.

breast-cancer-screening radiology medical-imaging diagnostic-support mammography-analysis

About Deep-Learning-Approaches-for-Enhanced-Breast-Cancer-Detection

harshjuly12/Deep-Learning-Approaches-for-Enhanced-Breast-Cancer-Detection

A deep learning project aimed at early detection of breast cancer by classifying tumors as benign or malignant based on features extracted from cell images. The project demonstrates data preprocessing, model training, and evaluation using various deep learning algorithms to achieve high accuracy in predictions.

This project helps medical professionals identify breast cancer by analyzing features extracted from cell images. It takes raw cell image data and outputs a classification of tumors as either benign or malignant, aiding in early detection. This tool is designed for pathologists, oncologists, and other medical practitioners involved in cancer diagnosis.

cancer-detection medical-diagnosis pathology oncology diagnostic-imaging

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