Prostate Cancer Analysis Using a GNN-LSTM Hybrid Algorithm

A prostate cancer analysis system that uses a GNN-LSTM hybrid algorithm.

A prostate cancer analysis system that uses a GNN-LSTM hybrid algorithm. It is offered as a reference project: a complete, worked example of how a system like this is designed, built and evaluated, so that a developer can study it, run it and learn from it.

It suits learners who want to work with neural networks end to end: preparing datasets, designing and training a model, tuning it, evaluating it properly and explaining the outcome.

The main parts are dataset preparation and augmentation, model design and training, evaluation with standard metrics, plus error analysis, and a simple interface or API to try the model. The reference build uses PyTorch Geometric, Python, PyTorch, TensorFlow, and NumPy, with a clear project structure, setup instructions and sample data so that it can be run and extended.