Interpretable miRNA-based prediction model for early detection of pancreatic cancer: Development and cross-platform validation
Yanfei Zhu, Linglin Zhu, Yumei Liu, Yongshuo Ji, Junqiu Zhu, Hong Zhao · 2026
Read Interpretable miRNA-based prediction model for early detection of pancreatic cancer: Development and cross-platform validation by Yanfei Zhu, Linglin Zhu, Yumei Liu, Yongshuo Ji, Junqiu Zhu, Hong 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-13138659.txt.
Description
Yanfei Zhu and five co-authors build a prediction model in 2026 for catching pancreatic cancer early. The cancer kills so often because it is found late. Tiny RNA markers in blood, called miRNAs, could flag it sooner, but earlier models rarely proved themselves on fresh data or explained their calls.
Their model reads a signature of twenty such markers, trained on public data sets with eight hundred one samples. Scores stayed strong across separate test sets built on other platforms, from sequencing to direct assays. A ranking method named the markers that drove each call. The team presents the model as an explainable aid for early screening.
Catalog record
| CREATOR | Yanfei Zhu, Linglin Zhu, Yumei Liu, Yongshuo Ji, Junqiu Zhu, Hong Zhao |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 38 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |