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

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening

Breast Cancer predictor using Machine Learning Algorithm

Predict Breast Cancer Wisconsin (Diagnostic) using Naive Bayes

Clusterização dos dados presentes no dataset de câncer de mama, implementando os algoritmos K-means, algoritmo do cotovelo (elbow method) e da silhueta média (Silhouette).

3D-GMIC: an efficient deep neural network to find small objects in large 3D images

Breast cancer diagnoses with four different machine learning classifiers (SVM, LR, KNN, and EC) by utilizing data exploratory techniques (DET) at Wisconsin Diagnostic Breast Cancer (WDBC) and Breast Cancer Coimbra Dataset (BCCD).

Breast cancer prediction🎗️using logistic regression, random forest and artificial neural network

Breast Cancer Classification

breast cancer detection using KNN and SVM

Objective: To find if a given cancer specimen is malignant or benign using supervised machine learning algorithm- SVM (support vector machine)

Classification of Breast Cancer diagnosis Using Support Vector Machines

An experiment using neural networks to predict obesity-related breast cancer over a small dataset of blood samples.

Automating breast cancer diagnosis using histological data

Comparison of PCA, Linear Regression and Logistic Regression method in terms of accuracy and error rate for breast cancer dataset

Breast Cancer Detection

📉 Data Visualisation