Multiple Clustering Algorithms for Ovarian Cancer Subtyping (MCAOCS): identifying clinical phenotypes and treatment response in critical care
Yamin Qiu, Zhengwen Qin, Huixian Zheng, Tao Wang, Runhong Liu, Jing Yang · 2026
Read Multiple Clustering Algorithms for Ovarian Cancer Subtyping (MCAOCS): identifying clinical phenotypes and treatment response in critical care by Yamin Qiu, Zhengwen Qin, Huixian Zheng, Tao Wang, Runhong Liu, Jing Yang (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/PMC13523494.txt.
Description
Yamin Qiu and others develop, in a 2026 study, a grouping method to split very ill ovarian cancer patients into clear subtypes. Patients with this cancer in intensive care vary widely, which clouds outlook and care. The team applied several grouping methods together to medical data of many kinds.
Two intensive care data banks supplied 448 patients. Analysis of the first group gave two phenotypes. One, labeled Critical, showed shaky blood flow and was far sicker, while the other, labeled Stable, kept organ function. The split held up in the external cohort. Critical patients died at higher rates from 28 days through one year. Treatment patterns differed by subtype, although the authors stress those links are early hints rather than causal. They propose the binary system for sorting risk in the ICU.
Catalog record
| CREATOR | Yamin Qiu, Zhengwen Qin, Huixian Zheng, Tao Wang, Runhong Liu, Jing Yang |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 46913 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |