Predicting kinesiophobia in knee osteoarthritis: a head-to-head comparison between machine learning and traditional regression models
Xintong Li, Xiaoyu Huang, Yabing Han, Qianyun Zhang, Shigang Mao, Taolin Zhang, Yang Yu, Junjie Jiang · 2026
Read Predicting kinesiophobia in knee osteoarthritis: a head-to-head comparison between machine learning and traditional regression models by Xintong Li, Xiaoyu Huang, Yabing Han, Qianyun Zhang, Shigang Mao, Taolin Zhang, Yang Yu, Junjie Jiang (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/PMC13474673.txt.
Description
Xintong Li and colleagues compare prediction styles in 2026 for fear of movement in people with knee arthritis. Fear of movement can lock patients into inactivity that worsens pain. A group of 590 patients from one hospital was split into training and test sets. Five factors, led by pain intensity and pain catastrophizing, fed a simple chart model, and seven machine methods were built beside it.
The chart model scored well on both sets, while one machine method edged it only slightly on the test set. Importance plots confirmed pain level and catastrophic thinking as the top drivers. A clear chart that staff can read at a glance may serve clinics nearly as well as black-box tools. Both routes flag who needs fear-focused support.
Catalog record
| CREATOR | Xintong Li, Xiaoyu Huang, Yabing Han, Qianyun Zhang, Shigang Mao, Taolin Zhang, Yang Yu, Junjie Jiang |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 38680 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |