Scikit-Learn Supervised Machine Learning for Breast Cancer Binary Classification

You can view the codes and outputs from this link

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

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.

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

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

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,

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

LogisticRegression for breast cancer dataset

A mini project on Logistic Regression study

SDG generates synthetic breast cancer patient data

NTU Deep Learning Medical Image course

Breast Cancer Wisconsin Dataset Classifier with Scikit-learn and Streamlit

Imoto, H., Zhang, S. & Okada, M. A Computational Framework for Prediction and Analysis of Cancer Signaling Dynamics from RNA Sequencing Data—Application to the ErbB Receptor Signaling Pathway. Cancers (Basel). 12, 2878 (2020).

Predict Breast Cancer Wisconsin (Diagnostic) using Naive Bayes

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.

Artificial Inteligence to predict Breast Cancer