Classification of Breast Cancer diagnosis Using Support Vector Machines

Classifying malignant and benign tumors using Neural Networks 🔬

Chinese Mammography Database (CMMD dataset) Deep Learning Classification Pipeline

Python Data Analytics, Machine Learning & Natural Language Processing

Breast cancer detection using machine learning with deployment of model

This analysis aims to observe which features are most helpful in predicting malignant or benign cancer and to see general trends that may aid us in model selection and hyper parameter selection.

Classifying Breast Cancer Molecular Subtypes

This project is a part of research on Breast Cancer Diagnosis with Machine Learning algorithm using data-driven approaches. The final outcomes of the research were later published at an IEEE Conference and added to IEEE Xplore Digital Library.

Breast cancer is the most common form of cancer in women, and invasive ductal carcinoma (IDC) is the most common form of breast cancer. Accurately identifying and categorizing breast cancer subtypes is an important clinical task, and automated methods can be used to save time and reduce error. The goal of this script is to identify IDC when it i…

breast cancer detection using KNN and SVM

Breast Cancer lump classification using CNN

Artificial Neural Network - Wisconsin Breast Cancer Detection

Detects stage of breast cancer.

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).

The objective of the project was to build various models and compare their prediction performance based on accuracy.

Deep Learning in Medicine Final Project

Prediction of Benign or Malignant Cancer Tumors

An AI-powered Web app to detect the presence of Invasive Ductal Carcinoma (IDC) in histopathology breast-tissue images

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