no code implementations • 5 May 2024 • Chaojie Zhang, Shengjia Chen, Ozkan Cigdem, Haresh Rengaraj Rajamohan, Kyunghyun Cho, Richard Kijowski, Cem M. Deniz
A transformer-based deep learning model, MR-Transformer, was developed for total knee replacement (TKR) prediction using magnetic resonance imaging (MRI).
no code implementations • 29 Apr 2024 • Ozkan Cigdem, Shengjia Chen, Chaojie Zhang, Kyunghyun Cho, Richard Kijowski, Cem M. Deniz
A survival analysis model for predicting time-to-total knee replacement (TKR) was developed using features from medical images and clinical measurements.
1 code implementation • 14 Oct 2022 • Shengjia Chen, Nikunj Gupta, Woodward B. Galbraith, Valay Shah, Jacopo Cirrone
This study introduced a Drug Response Prediction (DRP) framework with two main goals: 1) design a data processing pipeline to extract information from tabular clinical data, and then preprocess it for functional use, and 2) predict RA patient's responses to drugs and evaluate classification models' performance.