This repository contains all the data analytics projects that I've worked on in python.
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Updated
Dec 9, 2022 - Jupyter Notebook
This repository contains all the data analytics projects that I've worked on in python.
Classification of Breast Cancer diagnosis Using Support Vector Machines
Machine learning classifier for cancer tissues 🔬
Machine learning is widely used in bioinformatics and particularly in breast cancer diagnosis. In this project, certain classification methods such as K-nearest neighbors (K-NN) and Support Vector Machine (SVM) which is a supervised learning method to detect breast cancer are used.
This CNN is capable of diagnosing breast cancer from an eosin stained image. This model was trained using 400 images. It has an accuracy of 80%
Official code for Breast Cancer Histopathology Image Classification and Localization using Multiple Instance Learning
Multiple disease prediction such as Diabetes, Heart disease, Kidney disease, Breast cancer, Liver disease, Malaria, and Pneumonia using supervised machine learning and deep learning algorithms.
Breast Cancer Detection classifier built from the The Breast Cancer Histopathological Image Classification (BreakHis) dataset composed of 7,909 microscopic images.
This project uses mammograms for breast cancer detection using deep learning techniques.
Sistem Cerdas Prediksi Penyakit Kanker Payudara
Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slides, BCNB Dataset
Predicting the Stage of Breast Cancer - M (Malignant) and B (Benign) using different Machine learning models and comparing their performance.
Breast cancer detection using 4 different models i.e. Logistic Regression, KNN, SVM, and Decision Tree Machine Learning models and optimizing them for even a better accuracy.
We used different machine learning approaches to build models for detecting and visualizing important prognostic indicators of breast cancer survival rate. This repository contains R source codes for 5 steps which are, model evaluation, Random Forest further modelling, variable importance, decision tree and survival analysis. These can be a pipe…
Predicting survival outcome in breast cancer patients based on their gene expression
Classification of Breast Lesion contours to Benign and Malignant Categories.
A text-based computational framework for patient -specific modeling for classification of cancers. iScience (2022).
A machine learning process to distinguish good from bad breast cancer.
Predicts whether the type of breast cancer is Malignant or Benign
Breast Cancer Prediction using fuzzy clustering and classification
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