Fraction of Genome Altered, Age, Microsatellite Instability Score, Tumor Mutational Burden, Cancer Type, Metastasis Status, and Choice of Cancer Therapy Predict Overall Survival in Multiple Machine Learning Models
Background/Objectives: The accurate prediction of overall survival (OS) in cancer patients is crucial for personalized treatment strategies. Methods: In this study, we developed machine learning models to predict OS by integrating clinical and mutational features from a cohort of 25,508 cancer patie...
Saved in:
| Main Author: | Guillaume Mestrallet |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-02-01
|
| Series: | Onco |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-7523/5/1/8 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Computed tomography radiomics to predict microsatellite instability status and immunotherapy response in gastric cancer
by: Zhou Li, et al.
Published: (2025-08-01) -
Tislelizumab-induced hemophagocytic lymphohistiocytosis in a patient with microsatellite instability-high colon cancer and coexisting systemic lupus erythematosus: a case report and literature review
by: Pengqing Jiao, et al.
Published: (2025-08-01) -
Gynecologic and obstetric complications in women with congenital fibrinogen disorders: insights from the Prospective Rare Bleeding Disorders Database
by: Samin Mohsenian, et al.
Published: (2025-07-01) -
Calcium ion-binding genes can predict tumor mutation burden and immune checkpoint blockade response in a pan-cancer model
by: Wan-Yu Lin, et al.
Published: (2025-07-01) -
Certain pMMR colorectal cancer patients should undergo additional MSI-PCR testing to reduce the risk of misdiagnosing MSI-H and Lynch syndrome
by: Jinglin Huang, et al.
Published: (2025-07-01)