This repo is dedicated to the medical reserach for skin and breast cancer and brain tumor detection detection by using NN and SVM and vgg19

Develop a deep learning-based model for accurate image-to-image translation across MRI sequences for the brain region.

Solution for the precisionFDA Brain Cancer Predictive Modeling Challenge using msaenet

My Solution for PrecisionFDA Brain Cancer Predictive Modeling and Biomarker Discovery Challenge

Survival Prediction of GlioBlastoma Patients using Ensemble architecture of random forest, xgboost and logistic regression classifiers. Uses Optuna for tuning, SMOTE for imbalances, CNN for feature extraction, LDA for feature pre-processing, MPL and Seaborn for visualizations and concordance index as the performance metrics.

Brain cancer classification with 98.2% accuracy

This project was developed as a solution to medical science which aims to classify different types of brain cancers using cutting edge advanced deep learning techniques.

Accurate Early Detection of GBM Brain Cancer With Deep Learning (AI) - Silver Medal Finalist at GVRSF 2019

🔬🧠 Intraoperative deep learning-based detection of high grade glioma with optical coherence tomography

This project leverages artificial intelligence to address ethical and privacy concerns in healthcare by generating synthetic brain cancer images. The goal is to create a synthetic dataset that closely resembles real data, enabling effective training of machine learning models without compromising patient privacy.

A small brain cancer detector, AI class assignment

MRI scans, tumor classification.

In this project, we will implement and compare ResNet, AlexNet and MLP on brain cancer T2-weighted MRI image.