Machine learning-based prognostic model integrating preoperative HALP score and lactate dehydrogenase for predicting postoperative recurrence of prostate cancer
Hao Wang, Xuemeng Qiu, Zhen Li, Jiyue Wu, Lijian Gan, Dawei Xie, Yirui Wei, Jianwen Wang, Wei Wang · 2026
Read Machine learning-based prognostic model integrating preoperative HALP score and lactate dehydrogenase for predicting postoperative recurrence of prostate cancer by Hao Wang, Xuemeng Qiu, Zhen Li, Jiyue Wu, Lijian Gan, Dawei Xie, Yirui Wei, Jianwen Wang, Wei 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/pmc-13393940.txt.
Description
Hao Wang and others build math models to guess prostate cancer return after surgery in a 2026 study. Blood-test return after prostate removal stays a hard test, and old risk charts guess it poorly.
The team took in 320 men at a main site, 125 with return, and checked the models on 144 men elsewhere, testing ten learning methods on exam, blood, and food-plus-defense traits. A plain model that joins a nutrition-defense score with a lactate enzyme was built for sorting risk man by man. Urologists gain a workable tool for picking who needs close watch after surgery.
Catalog record
| CREATOR | Hao Wang, Xuemeng Qiu, Zhen Li, Jiyue Wu, Lijian Gan, Dawei Xie, Yirui Wei, Jianwen Wang, Wei Wang |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 41 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |