Scikit-Learn Supervised Machine Learning for Breast Cancer Binary Classification

Phylogenies of Breast Cancer Brain Metastases

This Python Project aims to implement an AI convolutional neural network for the classification of breast cancer screenings for the aquisition of the bachelors degree. It is based on the Kaggle CBIS-DDSM: Breast Cancer Image Dataset.

Este repositório contém implementações de redes neurais para a classificação de câncer de mama. Este projeto utiliza o conjunto de dados da UCI sobre câncer de mama. Três abordagens distintas, implementadas em Python com Keras, exploram desde modelos simples até técnicas avançada de validação cruzada e sintonização de hiperparâmetros.

Independent evaluation of a multi-view multi-task convolutional neural network breast cancer classification model using Finnish mammography screening data

Official repository of "Simulating Dynamic Tumor Contrast Enhancement in Breast MRI using Conditional Generative Adversarial Networks"

You can view the codes and outputs from this link

Repository for our limited angle deep learning based DOT image reconstruction

Streamlit AI App for Triaging and Segmenting Breast MRI

Real world data was modeled to predict if the patient had benign or malignant breast cancer using K-Nearest-Neighbors and SVM Classifiers.

Determination of whether a tumor is malignant or benign. Accuracy is 97.37%

Addresses the problem of reconstructing images acquired by diffuse optical tomography using deep learning.

Python package to access Breast Cancer Gene Expression data

Machine Learning project for breast cancer detection

AI Breast cancer detection using InBreast, CBIS-DDSM, MIAS mammography image datasets

Logistic regression model to predict the survival of patients who had undergone surgery for breast cancer.

Repository for our deep multitask paper in DOT imaging.

An adaptable method for analyzing SNVs, INDELs, and CNVs from Whole Exome Sequencing (WES) data, emphasizing germline variants.

Welcome to the official repository of HF-Fed: Hierarchical based customized Federated Learning Framework for X-Ray Imaging accepted in MICCAI Worshop 2024.

Repository for method to analyse the relationship between germline variants and somatic mutations and alternative splicing in breast cancer patients based on RNA-Seq data,