cancerSCOPE, a python library for cancer diagnosis

Performing Cancer Diagnosis via an Isoform Level Expression Ranking-based LSTM Model

This repository contains the codes for reproducing the results obtained by out DeepHistoPathology model for Ivasive Ductal Carcinoma open Dataset cancer detection

Glioblasted is a machine learning model to assist in the detection of glioblastoma multiforme, a high-grade, aggressive form of central nervous system cancer.

Project focuses on diagnosing cancer through image analysis. It utilizes machine learning models and techniques to analyze medical images and classify cancerous cells or tumors. It aims to improve cancer diagnosis accuracy and assist healthcare professionals.

Cancer diagnosis (using supervised machine learning and AI to determine whether tumor is malignant or benign)

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.