This paper is in the following e-collection/theme issue:

mHealth for Telemedicine and Homecare (554) Telehealth and Telemonitoring (2170) Mobile Apps for Cancer Care and Cancer Prevention and Screening (278) Artificial Intelligence (2308) Theme Issue 2025: Artificial Intelligence in Oncology (11) Internet for Rehabilitation (96) Postoperative Monitoring and Telemonitoring (209)

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

Authors of this article:

Tong Wu1 Author Orcid Image ;   Ting Han1, 2, 3 Author Orcid Image ;   Xiaoju Zhang4, 5 Author Orcid Image ;   Yumei Dai4, 5 Author Orcid Image ;   Xiaoyan Meng4, 5 Author Orcid Image
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