Breast Cancer and Density Classification Using Deep Learning Models
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Updated
Apr 30, 2019 - Jupyter Notebook
Breast Cancer and Density Classification Using Deep Learning Models
A structural equation modeling approach for the identification of gene expression adaptation in breast cancer patients at grade specific level
Algorithm used: Logistic Regression, Decision Tree Classifier, Random Forest Classifier and Support Vector Machine.
Mass Detection in Breast Using Transfer Learning for Computer Aided Diagnosis
Patato Classification,Breasr Cancer detection,Human Activity Recognition
iPython notebook using sklearn to predict breast cancer using logistic regression
This Python script uses TensorFlow to build, train, and evaluate a neural network for breast cancer diagnosis. It processes a dataset (cancer.csv), splits it into training and testing sets, and defines a sequential model with three sigmoid-activated dense layers. Users can train the model or evaluate it via an interactive command-line interface.
[IJHCS] UTA7: a dataset of time-on-task during our user studies extracted from clinicians while interacting with our assistant across the breast cancer diagnosis.
An automated CAD (Computer aided diagnosis) system for the classification of the breast histopathology images. It contains machine learning (feature extraction) and deep learning (transfer learning) pipelines.
A website for spreading awareness against Breast Cancer.
Bra Perfect helps you find your ideal bra in seconds. The shape, size, position, symmetry, spacing, firmness and amount of relaxation of individual women's breasts vary considerably, and this app proves to be a useful tool for calculating your bra size.
An open source algorithm to generate a 3D model of the women bra. This allows ONEBra to build personalized/customized cups for symmetric breast restoration starting from a simple 3D photo.
K means clustering for breast-cancer-wisconsin.data from scratch
Este repositorio presenta una implementación de segmentación de mamas utilizando YOLOv8. La segmentación de mamas es crucial en el diagnóstico de cáncer de mama. El proyecto incluye un notebook detallado y una demostración desplegada para probar el modelo en tiempo real.
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