Machine learning and microbiome analysis for early detection of pancreatic cancer
Sogol Tavanaeian, Mohammad Mehdi Feizabadi, Sarvenaz Falsafi, Hamid Asadzadeh Aghdaei · 2025
Read Machine learning and microbiome analysis for early detection of pancreatic cancer by Sogol Tavanaeian, Mohammad Mehdi Feizabadi, Sarvenaz Falsafi, Hamid Asadzadeh Aghdaei (2025) 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-13081413.txt.
Description
Sogol Tavanaeian and co-authors hunt pancreatic cancer in mouth and gut microbes, hoping to catch a killer early. Pancreatic cancer kills reliably, with five-year survival near twelve percent, largely because it is found late and its signs are vague. Certain bacteria have been tied to its risk. Their 2025 paper builds machine learning models reading clinical and microbial clues together.
The data were small: twenty patients and twenty controls. Five classifiers were tested under cross-checking repeated two hundred times, with penalties to keep the models honest. Age alone separated the groups almost perfectly, and a ratio between two gut bacteria separated them completely in this sample. Models joining age to that ratio scored at the top of the scale. The authors package them as nomograms clinicians could use, while the cohort warns how far the proof has to travel.
Catalog record
| CREATOR | Sogol Tavanaeian, Mohammad Mehdi Feizabadi, Sarvenaz Falsafi, Hamid Asadzadeh Aghdaei |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 30 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |