Retraction Note: Improving stroke risk prediction by integrating XGBoost, optimized principal component analysis, and explainable artificial intelligence
Lesia Mochurad, Viktoriia Babii, Yuliia Boliubash, Yulianna Mochurad · 2026
Read Retraction Note: Improving stroke risk prediction by integrating XGBoost, optimized principal component analysis, and explainable artificial intelligence by Lesia Mochurad, Viktoriia Babii, Yuliia Boliubash, Yulianna Mochurad (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/PMC13270546.txt.
Description
Lesia Mochurad and co-authors are named on a 2026 retraction note in BMC Medical Informatics and Decision Making. The note withdraws their 2025 article on improving stroke risk prediction with machine learning methods named XGBoost, a stepwise data-reduction method, and explainable artificial intelligence.
Editors said worries had been raised about where the two public data sets used in the study came from and whether they could be trusted. Ethical oversight, the presence of details that could identify people, and checked clinical diagnoses could not be confirmed, and the authors gave no further proof. The editors therefore lost trust in the results. Mochurad did not state a position, and the other authors did not reply.
Catalog record
| CREATOR | Lesia Mochurad, Viktoriia Babii, Yuliia Boliubash, Yulianna Mochurad |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 1444 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |