In this project we create a deep learning neural network based on the proposed architecture in the Acute Leukemia Classification Using Convolution Neural Network In Clinical Decision Support System paper, built using Tensorflow 2.

In this project, ALL-IDB1 from the Acute Lymphoblastic Leukemia Image Database for Image Processing dataset by Fabio Scotti is used. We will use data augmentation to increase the amount of training and testing data we have.

We have tested our model on a number of different hardwares, including Intel® CPUs & NVIDIA GPUs with results varying between CPU & GPU. Tests show further investigation into seeding and randomness introduced to our network via the GPU software are required. For reproducible results every time, it is suggested to train on a CPU, although this obviously requires more time.

DISCLAIMER

These projects should be used for research purposes only. The purpose of the projects is to show the potential of Artificial Intelligence for medical support systems such as diagnosis systems.

Although the classifiers are accurate and show good results both on paper and in real world testing, they are not meant to be an alternative to professional medical diagnosis.

Developers that have contributed to this repository have experience in using Artificial Intelligence for detecting certain types of cancer. They are not a doctors, medical or cancer experts.

Please use this system responsibly.