Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/72560, first published .
A Telemedicine App for Nonrigid Facial Rehabilitation Training Enhanced by Efficient Fully Convolutional Neural Network With Residual Network (EffiFCNN-ResNet) to Improve Accessibility for Patients With Nasopharyngeal Carcinoma Cancer: Randomized Controlled Trial

A Telemedicine App for Nonrigid Facial Rehabilitation Training Enhanced by Efficient Fully Convolutional Neural Network With Residual Network (EffiFCNN-ResNet) to Improve Accessibility for Patients With Nasopharyngeal Carcinoma Cancer: Randomized Controlled Trial

A Telemedicine App for Nonrigid Facial Rehabilitation Training Enhanced by Efficient Fully Convolutional Neural Network With Residual Network (EffiFCNN-ResNet) to Improve Accessibility for Patients With Nasopharyngeal Carcinoma Cancer: Randomized Controlled Trial

Tong Wu   1 , PhD ;   Ting Han   1, 2, 3 , Prof Dr ;   Xiaoju Zhang   4, 5 , PhD ;   Yumei Dai   4, 5 , MSN ;   Xiaoyan Meng   4, 5 , BSN

1 School of Design, Shanghai Jiao Tong University, Shanghai, China

2 Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China

3 Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, China

4 Department of Nursing, Fudan University Shanghai Cancer Center, Shanghai, China

5 Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China

Corresponding Author:

  • Ting Han, Prof Dr
  • School of Design
  • Shanghai Jiao Tong University
  • 800 Dongchuan Road
  • Minhang District
  • Shanghai 200240
  • China
  • Phone: 86 13916099300
  • Email: hanting@sjtu.edu.cn