Human–AI collaboration for dysphagia rehabilitation from effectiveness to implementation complexity: a systematic review
Wenwen Yang, Sufang Li, Yifei Du, Mengran Chen, Funa Yang, Fan Zhang, Ji Zhao, Yanqing Li, Xiaoxia Xu · 2026
Read Human–AI collaboration for dysphagia rehabilitation from effectiveness to implementation complexity: a systematic review by Wenwen Yang, Sufang Li, Yifei Du, Mengran Chen, Funa Yang, Fan Zhang, Ji Zhao, Yanqing Li, Xiaoxia Xu (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/PMC13254208.txt.
Description
Wenwen Yang and colleagues review human-AI teamwork for swallowing therapy in a 2026 systematic review. Oropharyngeal dysphagia, trouble swallowing, affects over half of nerve and cancer patient groups, yet therapists are scarce. The review covered 31 studies with 1,012 participants who used AI-augmented rehabilitation.
AI support gave short-term gains in oral intake and body measures, but gains faded within weeks of stopping. Use also dropped sharply once clinician supervision ended. The biggest barrier, rated high in 61.3 percent, was the user side: digital skill, thinking limits, and interface ease. The authors back trials for supervised stroke care first.
Catalog record
| CREATOR | Wenwen Yang, Sufang Li, Yifei Du, Mengran Chen, Funa Yang, Fan Zhang, Ji Zhao, Yanqing Li, Xiaoxia Xu |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 184976 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |