Learning-based fully automated prediction of lumbar disc degeneration progression with specified clinical parameters and preliminary validation.

Jason Pui Yin CheungXihe KuangMarcus Kin Long LaiKenneth Man-Chee CheungJaro KarppinenDino SamartzisHonghan WuFengdong ZhaoZhaomin ZhengTeng Zhang

Published in: European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society (2021)

This is the first attempt of using deep learning to predict LDD progression on a large dataset with 5-year follow-up. Requiring no human interference, our pipeline can potentially achieve similar predictive performances in new settings with minimal efforts.

Keyphrases

deep learning
endothelial cells
machine learning
artificial intelligence
minimally invasive
convolutional neural network
induced pluripotent stem cells
high throughput