Beat breast cancer with machine learning!
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Updated
Jun 30, 2018 - Python
Beat breast cancer with machine learning!
Breast density classification with deep convolutional neural networks
The aim of this project is to apply Bayesian Machine Learning Algorithm to predict the diagnosis condition of the patients.
Worked with Dr. Shandong Wu at University of Pittsburgh to use software to improve outcomes for breast cancer risk detection.
📉 Data Visualisation
Breast Cancer Detection
Comparison of PCA, Linear Regression and Logistic Regression method in terms of accuracy and error rate for breast cancer dataset
Automating breast cancer diagnosis using histological data
An experiment using neural networks to predict obesity-related breast cancer over a small dataset of blood samples.
Classification of Breast Cancer diagnosis Using Support Vector Machines
Objective: To find if a given cancer specimen is malignant or benign using supervised machine learning algorithm- SVM (support vector machine)
breast cancer detection using KNN and SVM
Breast Cancer Classification
Breast cancer prediction🎗️using logistic regression, random forest and artificial neural network
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).
3D-GMIC: an efficient deep neural network to find small objects in large 3D images
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).
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