heyzhanghaha / PregGAN

PreGAN source code

PregGAN

This repository contains the implementation for PregGAN. Based on the characteristics of GAN, we developed its ability as a disease prognosis prediction model, and designed PregGAN to predict the survival time of breast cancer patients.

PregGAN structure

The structure diagram of PregGAN is shown in the figure below.

PregGAN hyperparameters

The hyperparameters of the neural network in the generator and discriminator of PregGAN are shown in the following table.

	Layer	Detail	Input Sizes	Output sizes
	Fully connected layer	BatchNorm,ReLU	50	64
	Fully connected layer	BatchNorm,ReLU	64	128
Generator	Fully connected layer	BatchNorm,ReLU	128	64
	Fully connected layer		64	1
	Sigmoid		1	1
	Fully connected layer	BatchNorm,LeakyReLU	31	64
Discriminator	Fully connected layer	BatchNorm,LeakyReLU	64	128
	Fully connected layer	BatchNorm,LeakyReLU	128	64
	Fully connected layer		64	1

Requirements

The environment can be set up using Anaconda with the following commands:

conda create --name preggan-pytorch python=3.6
conda activate preggan-pytorch
pip install torch==1.8.2+cu102 torchvision==0.9.2+cu102 torchaudio===0.8.2 -f https://download.pytorch.org/whl/lts/1.8/torch_lts.html
pip install -r requirements.txt

Training

cd ..\PregGAN
jupyter notebook

• Run the code blocks in order after opening the jupyter notebook.