Letter to the Editor: Quantifying outcome gains in AI-empowered rehabilitation models
This letter addresses the review by Liu and Xie on AI-empowered rehabilitation models, specifically regarding the integration of real-time assessments and adaptive interventions. While the authors present compelling figures about recovery time reduction and increased adherence in AI models, the basis for these figures remains unclear. The letter requests clarification on the sources and definitions of these metrics, such as recovery time and adherence, and how they relate to algorithm performance and clinical outcomes. A more precise mapping of the quantified claims to specific sources would improve the clarity and applicability of the proposed model for clinical use.
Authors
- Lixin Zhang
- Yanmei Yin
Institutions
- China Medical University (CN)
Publication Details
- Journal
- SLAS TECHNOLOGY
- Published
- 2026-03-01
- DOI
- https://doi.org/10.1016/j.slast.2026.100414
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00