GitHub topics: breast-cancer

Repositories

Habib-AAhsan/TensorTrapX_mh

TensorTrapX_mh is a production-ready machine learning framework for breast cancer diagnosis. Built with TensorFlow, FastAPI, and Redis, it supports real-time prediction, SHAP/LIME explainability, asynchronous feedback collection, and Prometheus/Grafana monitoring.

Language: Jupyter Notebook - Size: 2.91 MB - Last synced at: about 20 hours ago - Pushed at: about 22 hours ago - Stars: 0 - Forks: 0

minotikedare/Breast-Cancer-Prediction-Using-Machine-Learning

Breast Cancer Prediction

Language: Jupyter Notebook - Size: 3.77 MB - Last synced at: 3 days ago - Pushed at: 4 days ago - Stars: 0 - Forks: 0

waghmareaniket/Pytorch-using-Breast-cancer-in-Deep-learning

breast cancer prediction model using PyTorch. It preprocesses the dataset, encodes labels, and trains a neural network on the features. Finally, it evaluates the model's performance on test data to classify tumors as malignant or benign.

Language: Jupyter Notebook - Size: 67.4 KB - Last synced at: 3 days ago - Pushed at: 4 days ago - Stars: 0 - Forks: 0

Marval96/Transcriptomics_UIVC

Transcriptomics analysis (RNAseq bulk) of macrophages in the breast cancer tumour microenvironment (BrCa).

Language: Jupyter Notebook - Size: 12.8 MB - Last synced at: 5 days ago - Pushed at: 5 days ago - Stars: 3 - Forks: 2

satyajeetparmar0/image-classification-cnn

🧠 Image Classification using CNN & VGG16 | Medical Image Analysis | TensorFlow & Keras

Language: Jupyter Notebook - Size: 6.84 KB - Last synced at: 5 days ago - Pushed at: 5 days ago - Stars: 0 - Forks: 0

FMCalisto/FMCalisto

:crystal_ball: My Personal Open Source'rer Profile

Size: 23.7 MB - Last synced at: 7 days ago - Pushed at: 7 days ago - Stars: 5 - Forks: 4

naomifridman/BreastDCEDL

BreastDCEDL Pretreatment MRI scans of 2070 Breast cancer patients. A Deep Learning-Ready DCE-MRI Breast Cancer Dataset from I-SPY2 and I-SPY1 trials (1,2 and DUKE.

Language: Jupyter Notebook - Size: 1.05 GB - Last synced at: 8 days ago - Pushed at: 9 days ago - Stars: 6 - Forks: 3

MIMBCD-UI/meta

:paperclip: About MIMBCD-UI Project

Size: 1.04 GB - Last synced at: 9 days ago - Pushed at: 9 days ago - Stars: 12 - Forks: 4

Nasim-Khalili/Cancer-with-Classification

this project applies multiple machine learning algorithms to classify breast cancer tumors as benign or malignant based on medical data.

Size: 1.95 KB - Last synced at: 2 days ago - Pushed at: 5 months ago - Stars: 2 - Forks: 0

adrenaline555/KizBasina_Odev2

Breast Cancer Classification using the Wisconsin dataset. Predict benign or malignant tumors with models. Explore data preprocessing and performance comparison. 🦠📊

Language: Python - Size: 309 KB - Last synced at: 10 days ago - Pushed at: 10 days ago - Stars: 0 - Forks: 0

Jonghwan-dev/Awesome-Segmentation-in-Medical

Welcome, Awesome-segmentation-in-medical project. This repo is robust, reproducible, and fair benchmarking framework for breast ultrasound (BUS) image segmentation. Features 10+ models (UNet, UNet++, TransUnet, SwinUnet etc.), 5+ datasets, and strict data separation to prevent test set leakage.

Language: Python - Size: 1.24 MB - Last synced at: 13 days ago - Pushed at: 13 days ago - Stars: 1 - Forks: 0

AICAN-Research/H2G-Net

🚀 H2G-Net: Segmentation of breast cancer region from whole slide images

Language: Jupyter Notebook - Size: 61.8 MB - Last synced at: 3 days ago - Pushed at: 14 days ago - Stars: 27 - Forks: 8

deliprofesor/KizBasina_Odev2

Breast Cancer Classification using Support Vector Machines (SVM) with multiple kernels. This project includes data preprocessing, exploratory data analysis, model training, hyperparameter tuning, handling imbalanced classes with SMOTE, and model evaluation using metrics like accuracy, confusion matrix, classification reports, and ROC-AUC curves.

Language: Python - Size: 320 KB - Last synced at: 14 days ago - Pushed at: 14 days ago - Stars: 0 - Forks: 0

MIMBCD-UI/prototype-breast-screening

💎 MIMBCD-UI Breast Screening Prototype

Language: JavaScript - Size: 109 MB - Last synced at: 15 days ago - Pushed at: 15 days ago - Stars: 1 - Forks: 1

mida-project/prototype-heatmap

[IJHCS] Assistive heatmaps prototype for promoting eXplainable AI (XAI) in the medical workflow for the breast cancer diagnosis. The work was published in the International Journal of Human-Computer Studies.

Language: JavaScript - Size: 323 MB - Last synced at: 15 days ago - Pushed at: 15 days ago - Stars: 3 - Forks: 0

DF-W/FINet

Frequency-aware Interaction Network for Ultrasound Image Segmentation (FINet)

Language: Python - Size: 166 KB - Last synced at: 16 days ago - Pushed at: 16 days ago - Stars: 3 - Forks: 0

jdutel42/MpBC_project

Spatial transcriptomics of MpBC. This project analyzes spatial transcriptomics data from 15 metaplastic breast carcinoma (MpBC) samples using 10x Genomics Visium. It aims to explore tumor heterogeneity and transdifferentiation, leveraging expert-labeled cell types to identify spatial clusters and biomarkers.

Language: Jupyter Notebook - Size: 650 MB - Last synced at: 19 days ago - Pushed at: 20 days ago - Stars: 0 - Forks: 0

monajemi-arman/breast_cancer_detection

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

Language: Python - Size: 754 KB - Last synced at: 20 days ago - Pushed at: 20 days ago - Stars: 6 - Forks: 2

BreastScreeningAI/breastscreeningai.github.io

Project website.

Language: CSS - Size: 122 MB - Last synced at: 21 days ago - Pushed at: 21 days ago - Stars: 1 - Forks: 0

raktim-mondol/GRAPHITE

State-of-the-art deep learning framework for breast cancer histopathology analysis combining graph-based representations with interpretable AI techniques for enhanced diagnostic insights and clinical decision support.

Language: Python - Size: 1.89 MB - Last synced at: 24 days ago - Pushed at: 24 days ago - Stars: 0 - Forks: 0

cbailes/awesome-ai-cancer

Awesome artificial intelligence in cancer diagnostics and oncology

Size: 169 KB - Last synced at: 5 days ago - Pushed at: almost 3 years ago - Stars: 153 - Forks: 53

DIDSR/tsynth-release

T-SYNTH is a synthetic digital breast tomosynthesis (DBT) dataset with four breast fibroglandular density distributions imaged using Monte Carlo x-ray simulations with the publicly available Virtual Imaging Clinical Trial for Regulatory Evaluation (VICTRE) toolkit.

Language: Jupyter Notebook - Size: 2.69 MB - Last synced at: 27 days ago - Pushed at: 27 days ago - Stars: 0 - Forks: 0

MIMBCD-UI/prototype-multi-modality

✨ [AVI 2020] A prototype platform for lesion annotations and manual segmentation on breast cancer diagnosis with a multimodality strategy. The work was presented in the Advanced Visual Interfaces (AVI) conference.

Language: JavaScript - Size: 7.65 MB - Last synced at: 28 days ago - Pushed at: 28 days ago - Stars: 6 - Forks: 1

tonyamf/Thesis_Breast_Cancer_Diagnosis_Screening_via_Deep_learning

Investigated Meta Pseudo Labels for breast cancer CAD. The pipeline failed because the baseline segmentation model could not learn from the extremely limited labeled data. This research demonstrates that it's success is contingent on first establishing a functional supervised model, a step that was ultimately hampered by severe data scarcity

Language: Jupyter Notebook - Size: 4.39 MB - Last synced at: 29 days ago - Pushed at: 29 days ago - Stars: 0 - Forks: 0

tirtha103/Breast-Cancer-Classification-using-Support-Vector-Machines-SVM-

Breast Cancer Classification using Support Vector Machines (SVM). Complete ML pipeline with preprocessing, EDA, hyperparameter tuning (C, gamma), GridSearchCV, decision boundary plots, and evaluation metrics.

Language: Jupyter Notebook - Size: 1.06 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

Yashmaini30/Breast-Cancer-Detection

Transfer learning-based breast cancer classification using ultrasound images. Includes ResNet-50, AlexNet, VGG16, and GoogLeNet with fine-tuning, feature extraction, and Bayesian optimization.

Language: Jupyter Notebook - Size: 9.3 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 1 - Forks: 0

nyukat/breast_cancer_classifier

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening

Language: Jupyter Notebook - Size: 222 MB - Last synced at: 26 days ago - Pushed at: over 1 year ago - Stars: 874 - Forks: 276

eddynorman/cancer_risk_assessment_app

An Application that enables its users to check if they are at a high risk of having breast/cervical cancer and if the risk is high they should go for further checkup

Language: Jupyter Notebook - Size: 11.7 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

smriti-joshi/muvi

MuVi: Official repository of "Single Image Test-Time Adaptation via Multi-View Co-Training" In MICCAI 2025.

Size: 886 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

Arka-Bhowmik/MRI_triage_app

Streamlit AI App for Triaging and Segmenting Breast MRI

Language: Python - Size: 3.65 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 1 - Forks: 0

Asifr001/BreastScanNN-Deep-Learning-for-Cancer-Classification

A deep learning model built with TensorFlow to classify breast cancer as benign or malignant based on clinical features.

Language: Jupyter Notebook - Size: 79.1 KB - Last synced at: about 1 month ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

srubin3/Breast_Cancer_Analysis

A data science project using the Breast Cancer Wisconsin Diagnostic Dataset to classify tumors as benign or malignant. Includes data cleaning, exploratory analysis, advanced visualizations, PCA, and Logistic Regression modeling. Demonstrates proficiency in Python, Scikit-learn, and structured analytics while addressing model overfitting challenges.

Language: Jupyter Notebook - Size: 2.06 MB - Last synced at: 17 days ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

RoySoumik23/AutoMutSig_Pipeline

The automation pipeline processes mutation and clinical data, aligning and cleaning the inputs before performing a detailed analysis. It enables visualization and interpretation of mutation signatures with a focus on specific genes and cancer subtypes.

Language: R - Size: 106 KB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 1

BreastCancerAI/Tensorflow-Quantum-IDC-Classifer-2020

A Quantum Neural Network built with Tensorflow Quantum and training on Breast Histopathology Images on Kaggle by Paul Mooney (Invasive Ductal Carcinoma)

Language: Python - Size: 1010 KB - Last synced at: about 1 month ago - Pushed at: over 5 years ago - Stars: 15 - Forks: 4

fedoxyz/BreastTumorPredictor

SAM-2 and classification model, training on ultrasonic images dataset for predicting and segmenting breast tumors

Language: Jupyter Notebook - Size: 178 MB - Last synced at: about 2 months ago - Pushed at: 8 months ago - Stars: 2 - Forks: 0

Steffi8868/SOLA25_BB103X

This GitHub repository contains the code used in the data analysis portion of the Bachelor's Degree Project: Identification of an Immune Infiltration Signature in Breast Cancer Subtypes and its Association with Tumor Clinicopathological Characteristics and Patient Outcome by Linn Berglund, Olivia Blomberg, Stephanie Mobedjina, & Alice Åhlund

Language: R - Size: 492 KB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

PathologyDataScience/MuTILs_Panoptic

Amgad M, Salgado R, Cooper LA. A panoptic segmentation approach for tumor-infiltrating lymphocyte assessment: development of the MuTILs model and PanopTILs dataset. medRxiv 2022.01.08.22268814.

Language: Python - Size: 266 KB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 19 - Forks: 4

smb-h/breast-cancer-patterns-association-rule-mining

Breast Cancer Pattern Recognition through Association Rule Mining

Language: Jupyter Notebook - Size: 3.24 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 4 - Forks: 1

RichardObi/mammo_dp

Official repository of "Enhancing the Utility of Privacy-Preserving Cancer Classification using Synthetic Data"

Language: Python - Size: 86.5 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 1

Anand-Ambastha/Breast_Cancer_Prediction_Using_NN

This project demonstrates the application of neural networks for binary classification in medical diagnosis. The model analyzes various features of cell nuclei to classify breast tumors as either malignant or benign, potentially assisting in early detection and diagnosis of breast cancer.

Language: Jupyter Notebook - Size: 424 KB - Last synced at: about 1 month ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

QendresaVisoka/AIRA

AI-powered assistant developed to support radiologists in the detection and segmentation of breast cancer in mammogram images

Language: Jupyter Notebook - Size: 584 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

rishiswethan/Cancer-detection-using-CNN

This CNN is capable of diagnosing breast cancer from an eosin stained image. This model was trained using 400 images. It has an accuracy of 80%

Language: Python - Size: 84.1 MB - Last synced at: 9 days ago - Pushed at: over 2 years ago - Stars: 65 - Forks: 37

ReusJimenez/breastcancer-data-analysis

Limpieza, transformación y EDA del dataset Breast Cancer Wisconsin para preparar datos médicos de tumores benignos y malignos para análisis predictivos. 🧬🩺

Language: Jupyter Notebook - Size: 857 KB - Last synced at: 15 days ago - Pushed at: 3 months ago - Stars: 1 - Forks: 0

nano-bot01/Breast-Cancer-Detection

Breast cancer detection using machine learning with deployment of model

Language: HTML - Size: 1.04 MB - Last synced at: 22 days ago - Pushed at: about 2 years ago - Stars: 9 - Forks: 0

akshaybahadur21/BreastCancer_Classification

Machine learning classifier for cancer tissues 🔬

Language: Python - Size: 21.2 MB - Last synced at: 26 days ago - Pushed at: about 4 years ago - Stars: 77 - Forks: 60

EMFMed/MERIT

Microwave Radar-based Imaging Toolbox (MERIT) is free and open-source software for microwave radar-basaed imaging. Including getting started guides and example data, MERIT is a flexible and extensible framework for developing, testing, running and optimising radar-based imaging algorithms.

Language: MATLAB - Size: 12 MB - Last synced at: 2 months ago - Pushed at: 12 months ago - Stars: 57 - Forks: 20

lnk99/breast-cancer-clustering

This project applies unsupervised machine learning techniques: KMeans, GMM, Spectral Clustering, and DBSCAN,to classify tumors using the Breast Cancer dataset. It benchmarks the clustering outcomes against a supervised SVM classifier, demonstrating strong diagnostic performance.

Language: Jupyter Notebook - Size: 1.99 MB - Last synced at: about 1 month ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

aydinnyunus/cancerdetection

Breast Cancer Detection

Size: 1000 Bytes - Last synced at: about 2 months ago - Pushed at: almost 6 years ago - Stars: 6 - Forks: 1

Moataz-Nasser/Breast-Cancer-Classification

This project focuses on using machine learning to classify breast cancer as malignant or benign. It evaluates multiple models, including Support Vector Classifier (SVC), Logistic Regression, and Random Forest, to compare their performance on the Breast Cancer Wisconsin (Diagnostic) Dataset. The main objective is to identify the most effective mode

Language: Jupyter Notebook - Size: 87.9 KB - Last synced at: about 2 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

RichardObi/SimulatingDCE

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

Language: Python - Size: 135 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 3 - Forks: 0

lyotvincent/CPMP

CPMP: AI-driven computational pathology for recurrence risk assessment in early-stage breast cancer

Language: Python - Size: 4.2 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

mrdvince/breast_cancer_detection

Breast Cancer Detection classifier built from the The Breast Cancer Histopathological Image Classification (BreakHis) dataset composed of 7,909 microscopic images.

Language: Python - Size: 30.4 MB - Last synced at: about 1 month ago - Pushed at: over 4 years ago - Stars: 67 - Forks: 23

mida-project/sa-uta7-recall-precision

[AIIM] Recall & Precision results of the UTA7 statistical analysis.

Language: HTML - Size: 293 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 1 - Forks: 0

DIDSR/VICTRE_PIPELINE

Home for the unified VICTRE pipeline for in silico breast imaging.

Language: C++ - Size: 23.9 MB - Last synced at: 2 days ago - Pushed at: 3 months ago - Stars: 24 - Forks: 14

Elysian01/Impulse-LifeSaviour

Flask based web app with five machine learning models on the 10 most common disease prediction, covid19 prediction, breast cancer, chronic kidney disease and heart disease predictions with their symptoms as inputs or medical report (pdf format) as input.

Language: HTML - Size: 1.24 MB - Last synced at: 3 months ago - Pushed at: over 2 years ago - Stars: 23 - Forks: 16

maladoi777/breast-cancer-prediction-app

A Streamlit web application for breast cancer prediction using logistic regression. Users can input key tumor features to receive real-time prediction and confidence scores based on the Breast Cancer Wisconsin Diagnostic Dataset.

Language: Jupyter Notebook - Size: 10.2 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

Mohammed-asaad-AI/Breast-Cancer-KNN-Comparison

A simple machine learning project comparing a manual K-Nearest Neighbors (KNN) implementation with Scikit-learn’s KNN classifier on breast cancer diagnosis data.

Language: Jupyter Notebook - Size: 93.8 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

andreped/DMDetect

Code relevant for training, evaluating, assessing, and deploying CNNs for image classification and segmentation of Digital Mammography images

Language: Jupyter Notebook - Size: 395 KB - Last synced at: 3 days ago - Pushed at: over 2 years ago - Stars: 9 - Forks: 1

QuantumCoderrr/PyCaret-BCDetection

🎗️ Breast Cancer Detection using PyCaret - a low-code machine learning pipeline. This project leverages automation and explainability to classify malignant and benign tumors from the Breast Cancer Wisconsin dataset. Built for simplicity, transparency, and clinical insight.

Language: HTML - Size: 885 KB - Last synced at: 29 days ago - Pushed at: 3 months ago - Stars: 1 - Forks: 0

PixelChicks/LifeAI

LifeAI: AI-Powered Support for Breast Cancer Patients

Language: Java - Size: 287 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 2 - Forks: 1

PixelChicks/LifeAIFrontend

LifeAI: AI-Powered Support for Breast Cancer Patients

Language: SCSS - Size: 2.87 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 2 - Forks: 1

abhipatel35/SVM-Hyperparameter-Optimization-for-Breast-Cancer

Utilizing SVM for breast cancer classification, this project compares model performance before and after hyperparameter tuning using GridSearchCV. Evaluation metrics like classification report showcase the effectiveness of the optimized model.

Language: Python - Size: 6.84 KB - Last synced at: 12 days ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

navyapatel2123/cancer_prediction

This project implements a machine learning model (Logistic Regression) trained on the Breast Cancer dataset to predict if a tumor is benign or malignant. It includes a Python script for training the model, a terminal-based prediction tool, and a web application built with Streamlit for interactive predictions.

Language: Python - Size: 60.5 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

Max-Artis-11/Deep-Neural-Network-for-Breast-Cancer-Classification

Build and train a neural network with PyTorch to classify breast cancer tumors as benign or malignant using the Breast Cancer Wisconsin (Diagnostic) dataset. This project is part of the IBM Deep Learning with PyTorch course on Coursera.

Language: Jupyter Notebook - Size: 173 KB - Last synced at: 5 days ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

iamandreatonina/Bachelor-s_thesis

Bachelor's Thesis UNITN, degree in Biomolecular Sciences and Technology

Size: 2.74 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

LidiaGarrucho/MAMA-MIA

The MAMA-MIA Dataset: A Multi-Center Breast Cancer DCE-MRI Public Dataset with Expert Segmentations

Language: Jupyter Notebook - Size: 8.1 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 40 - Forks: 2

gdg-a-coruna/Inteligencia-Artificial-en-la-Deteccion-del-Cancer

Repositorio con recursos sobre la charla Build with AI: Inteligencia Artificial en la Detección del Cáncer

Language: Jupyter Notebook - Size: 1.17 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 1 - Forks: 1

elaheghiyabi96/breast-cancer-prediction-mlp

Language: Jupyter Notebook - Size: 21.5 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

shibajyotidebbarma/Machine-Learning-with-Scikit-Learn-Breast-Cancer-Winconsin-Dataset

In this machine learning project I will work on the Wisconsin Breast Cancer Dataset that comes with scikit-learn. I will train a few algorithms and evaluate their performance. I will use ipython (Jupyter).

Language: Jupyter Notebook - Size: 347 KB - Last synced at: 26 days ago - Pushed at: about 6 years ago - Stars: 5 - Forks: 1

lerivera27/DEG-Analysis-BRCA

Differential Gene Expression or DEG specifically analyzing BRCA to identify genes with significant expression changes between normal and tumorous tissue.

Size: 13.7 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

MUHAMMADAKMAL137/Pytorch_Training_Pipeline_Using_Dataset_And_Dataloader_Class.ipynb

Binary classification of breast cancer using PyTorch. Used StandardScaler, LabelEncoder, Dataset, DataLoader, custom nn.Module model, BCELoss, and SGD. Focused on implementing a complete training pipeline, not optimizing accuracy.

Language: Jupyter Notebook - Size: 11.7 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

vkasojhaa/Clinical-Decision-Support-using-Machine-Learning

Predicting the Stage of Breast Cancer - M (Malignant) and B (Benign) using different Machine learning models and comparing their performance.

Language: Jupyter Notebook - Size: 3.48 MB - Last synced at: 26 days ago - Pushed at: almost 7 years ago - Stars: 13 - Forks: 10

dangnh0611/kaggle_rsna_breast_cancer

1st place solution of RSNA Screening Mammography Breast Cancer Detection competition on Kaggle: https://www.kaggle.com/competitions/rsna-breast-cancer-detection

Language: Python - Size: 83.4 MB - Last synced at: 3 months ago - Pushed at: over 1 year ago - Stars: 86 - Forks: 28

celiabenitez/mitonet-evaluation

MitoNet pipeline for predicting Ki-67 expression from H&E-stained breast cancer images

Language: Jupyter Notebook - Size: 27.3 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

MachineLearning4Work/DeepBreastCancer

Breast Cancer Histopathological Image Classification: A Deep Learning Approach

Language: Python - Size: 4.28 MB - Last synced at: 4 months ago - Pushed at: over 6 years ago - Stars: 8 - Forks: 1

Nasim-Khalili/Breast_Cancer-Decision_Tree

This project demonstrates the implementation of a **Decision Tree Classifier** to predict whether a breast cancer tumor is malignant or benign.

Language: Jupyter Notebook - Size: 4.43 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 1 - Forks: 0

nyukat/GMIC

An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization

Language: Jupyter Notebook - Size: 481 MB - Last synced at: 5 months ago - Pushed at: about 1 year ago - Stars: 173 - Forks: 49

rezariezqiaziz/Project-Machine-Learning-Breast-Cancer

This project contains an analysis of the Breast Cancer dataset from Scikit-Learn using Python. The analysis includes data exploration, visualization, and the implementation of machine learning models to classify tumors as malignant (cancerous) or benign (non-cancerous).

Language: Jupyter Notebook - Size: 875 KB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0

Sim98B/TabularDataGeneration

Synthetic Data Generation: Tabular & Medical Imaging. A comprehensive project focused on generating synthetic data for tabular datasets and medical imaging.

Language: Jupyter Notebook - Size: 214 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 1 - Forks: 0

tpnam0901/QTSeg

QTSeg: A Query Token-Based Architecture for Efficient 2D Medical Image Segmentation

Language: Jupyter Notebook - Size: 6.34 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 9 - Forks: 0

maliknaik16/publications

Research publications in Algorithms Optimization and Machine Learning

Size: 1.07 MB - Last synced at: 4 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

Preethi2805/Breast-Cancer-Classification

This project leverages Logistic Regression and Neural Networks to classify breast cancer cases as either malignant or benign. It demonstrates the power of machine learning in healthcare to assist in early diagnosis and decision-making.

Language: Jupyter Notebook - Size: 3.47 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0

nyukat/pathology_extraction

Improving Information Extraction from Pathology Reports using Named Entity Recognition

Language: Python - Size: 1.56 MB - Last synced at: 5 months ago - Pushed at: over 1 year ago - Stars: 14 - Forks: 2

kthuang20/ds4bio_project

Discovering Driver Genes for Triple-Negative Breast Cancer

Language: Jupyter Notebook - Size: 17.8 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

Likalto4/CEM-Detect

Implementation of the Deep Breath MICCAI 2024 workshop paper "ELK: Enhanced Learning through cross-modal Knowledge transfer for lesion detection in limited-sample contrast-enhanced mammography datasets"

Language: Jupyter Notebook - Size: 52.8 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

secrierlab/G0-breast-cancer-atlas

G0 breast cancer atlas

Language: R - Size: 320 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 1 - Forks: 1

nyukat/BIRADS_classifier

High-resolution breast cancer screening with multi-view deep convolutional neural networks

Language: Python - Size: 73 MB - Last synced at: 5 months ago - Pushed at: about 7 years ago - Stars: 155 - Forks: 59

nurulashraf/decisiontree-breastcancer

A practice project using the Breast Cancer dataset to build and evaluate classification and decision tree models. Includes data preprocessing, feature selection, model training, and performance evaluation. Ideal for exploring tree-based algorithms and their application in healthcare data analysis.

Language: Jupyter Notebook - Size: 1.14 MB - Last synced at: 5 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0