Predictive models for trans-stenotic pressure gradient in the transverse sinus based on multimodal correlates
Yan Huang, Linkun Cai, Xiaoyu Qiu, Chihang Dai, Xu Han, Guo-Peng Wang, Shusheng Gong, Zhenghan Yang, Heyu Ding, Zhenchang Wang, Pengfei Zhao · 2026
Read Predictive models for trans-stenotic pressure gradient in the transverse sinus based on multimodal correlates by Yan Huang, Linkun Cai, Xiaoyu Qiu, Chihang Dai, Xu Han, Guo-Peng Wang, Shusheng Gong, Zhenghan Yang, Heyu Ding, Zhenchang Wang, Pengfei Zhao (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/pmc-13654146.txt.
Description
Huang and co-authors build learning models that predict pressure drops across a narrowed brain vein without a catheter. The vein drains blood from the brain, and a tight stretch can raise pressure inside the skull. Direct pressure checks need an invasive probe, which limits their use.
The study drew on 83 patients at a Beijing hospital whose pressure had been measured between 2017 and 2022. Inputs joined clinical facts, lab values, and two kinds of scans, in all twenty-nine measures. Six learning methods were trained and compared. A sound non-invasive estimate could widen screening to patients who now skip the probe. It could also help pick who truly needs the invasive check. The team frames the models as a triage aid.
Catalog record
| CREATOR | Yan Huang, Linkun Cai, Xiaoyu Qiu, Chihang Dai, Xu Han, Guo-Peng Wang, Shusheng Gong, Zhenghan Yang, Heyu Ding, Zhenchang Wang, Pengfei Zhao |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 35 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |