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,
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Updated
Jun 10, 2024 - Python
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,
The Algorithm that powers up the Intellibra Kit
Independent evaluation of a multi-view multi-task convolutional neural network breast cancer classification model using Finnish mammography screening data
NTU Deep Learning Medical Image course
Segmentation of Breast Cancers using various segmentation loss functions
Histomic Prognostic Signature (HiPS): A population-level computational histologic signature for invasive breast cancer prognosis
Scikit-Learn Supervised Machine Learning for Breast Cancer Binary Classification
(MIDL 2023) Code for "Reverse Engineering Breast MRIs: Predicting Acquisition Parameters Directly from Images"
Breast Cancer Wisconsin Dataset Classifier with Scikit-learn and Streamlit
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.
An adaptable method for analyzing SNVs, INDELs, and CNVs from Whole Exome Sequencing (WES) data, emphasizing germline variants.
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.
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.
Dive into feature selection and classification with this Python repository, utilizing a genetic algorithm and various classifiers on a breast cancer dataset. Achieving high accuracy levels, SVM and ANN stand out with 97.37%. Ideal for machine learning enthusiasts and those interested in cancer diagnostics.
Code of the Stacking-Enhanced Bagging Ensemble Learning for Breast Cancer Classification with CNN on ICEEM 2023
Official repository for "Pre- to Post-Contrast Breast MRI Synthesis for Enhanced Tumour Segmentation"
🌸 Breast epithelium segmentation through IHC-guided supervision
Classification of whole-slide images based on tumor infiltrating lymphocyte grades using image-level labels
SDG generates synthetic breast cancer patient data
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