Machine Learning-Based Prediction Model for Type 2 Diabetic Peripheral Neuropathy: Role of Bilateral Brachial-Ankle Pulse Wave Velocity and Anthropometric Indicators
Zhengshan Zhang, Luying Sun, Yue Wang, Yahui Wang · 2026
Read Machine Learning-Based Prediction Model for Type 2 Diabetic Peripheral Neuropathy: Role of Bilateral Brachial-Ankle Pulse Wave Velocity and Anthropometric Indicators by Zhengshan Zhang, Luying Sun, Yue Wang, Yahui Wang (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/PMC13317770.txt.
Description
Zhengshan Zhang and colleagues built, in a 2026 study, a machine learning model to predict nerve damage in people with type 2 diabetes, a complication that creeps up silently. Their twist was adding artery stiffness readings from both ankles plus body shape measures to the usual clinical data.
Records for 966 patients, sorted by nerve conduction tests, fed nine competing models after a smart feature hunt found thirteen drivers. A support vector machine won, with accuracy of 0.74 and an AUC of 0.82 in the reported scores. Left-side pulse wave velocity dominated the rankings, far above its right-side twin, an asymmetry the authors flag as new. Wider hips looked protective, while smoking and long disease duration raised risk.
Catalog record
| CREATOR | Zhengshan Zhang, Luying Sun, Yue Wang, Yahui Wang |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 49669 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |