Prediction of Alzheimer’s disease by using deep learning 3D-Convolutional Neural Networks

We analyzed the T1 structural MRI by using deep learning 3D-CNN method. The results indicate that deep learning models can accurately predict AD patients with diagnostic accuracy of 96%. This can be achieved using raw MRI data, with a minimum of processing necessary to generate an accurate AD prediction. Our model shows highly sensitivity and negative predictive value and thus appropriate for use for screening testing in population study. Currently model has the potential to be used as a screen biomarker to investigate the neurodegeneration, brain aging and associated brain diseases.