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Abstract #3139

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

Na Sang1, Francisco M. Garcia2, Wanshun Wei3, Huabing Li4, Tao Ma1, and Silun Wang1

1YIWEI Medical Inc, Shenzhen, China, 2University of Massachusetts - Amherst, Amherst, MA, United States, 3YIWEI Meidcal Inc, Shenzhen, China, 4ZhongNan University, ChangSha, China

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.

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