Automated detection and classification of shoulder arthroplasty models using deep learning.

Paul H YiTae Kyung KimJinchi WeiXinning LiGregory D HagerHaris I SairJan Fritz

Published in: Skeletal radiology (2020)

DCNNs can accurately identify the presence of and distinguish between TSA & RTSA, and classify five specific TSA models with high accuracy. The proof of concept of these DCNNs may set the foundation for an automated arthroplasty atlas for rapid and comprehensive model identification.

Keyphrases

deep learning
loop mediated isothermal amplification
machine learning
artificial intelligence
convolutional neural network
single cell
high throughput
label free
quantum dots