brain-cancer

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.

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

Solution for the precisionFDA Brain Cancer Predictive Modeling Challenge using msaenet

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

Discovers actively recruiting neuro-oncology clinical trials (e.g., glioblastoma, brain tumors) and ranks them with simple, explainable heuristics. Web-page | App

MRI scans, tumor classification.

This R code utilises regression analysis to create a linear model to try and predict: 1. if a persons calorie consumption changes with age and 2. whether a patients survival differs by treatment type, plus what covariates have a significant influence on this

A small brain cancer detector, AI class assignment

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.

Comprehensive review of glioblastoma multiforme (GBM), a grade 4 brain cancer, covering subtypes, symptoms, treatments, causes, and lifestyle interventions. Includes full paper, references, and appendices for researchers and clinicians.

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

This project is an AI-powered Brain Tumor Detection System using Deep Learning and Computer Vision. The system analyzes Brain MRI images and predicts whether a tumor is present or not. The goal is to demonstrate how AI can assist medical image analysis through a user-friendly web application.

Research & Python models for the 2026 GBM study. Features the "Mechanical-Immunological Axis" (FUS + mRNA vaccines), Kaplan-Meier survival analysis, and clinical decision algorithms for precision neuro-oncology.

Scientific framework and immunological rationale for individualized brain tumor immunotherapy protocols.

Integrated strategies for Grade 4 Glioblastoma by Samuelson G. Combining molecular genomics, LIFU-mediated BBB disruption, and GKI-based metabolic conditioning to extend survival. Includes 2026 WHO standards and GKI protocols.

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