Precision medicine meets artificial intelligence: A new prognostic model for lower-grade glioma
Mohamed A Hammad, Hossam M Ashour · 2026
Read Precision medicine meets artificial intelligence: A new prognostic model for lower-grade glioma by Mohamed A Hammad, Hossam M Ashour (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-13571125.txt.
Description
Mohamed Hammad and Hossam Ashour discuss a new AI prognostic model for lower-grade glioma, in a 2026 commentary. These brain tumors vary wildly in outcome, and grading by microscope misses the molecular variety underneath. The commented study, by Jian and colleagues, fuses several data layers across four hundred forty-two tumor samples. The layers span messenger RNA, long non-coding RNA, methylation, and mutations. The team screened one hundred seventeen machine learning combinations.
The model splits patients into two subtypes with sharply different survival; the worse group also carries heavier immune infiltration. Forty-six hub genes carry the signature. The commentary praises the multi-omics ensemble as a step toward precision care and better guesses at who will answer immunotherapy. It also notes the field's habit of single-data models and their limited reach. The piece introduces the study to neuro-oncology readers.
Catalog record
| CREATOR | Mohamed A Hammad, Hossam M Ashour |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 7 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |