Machine learning algorithms able to predict the prognosis of gastric cancer patients treated with immune checkpoint inhibitors
The XGBoost model aided in identifying patients with GC who were more likely to benefit from ICIs therapy. Patient nutritional status may, to some extent, reflect prognosis.
Authors
- Mohan Wang (ORCID: https://orcid.org/0000-0003-4505-454X)
- Chun‐Su Yuan (ORCID: https://orcid.org/0000-0002-0711-2342)
- Hongwei Li (ORCID: https://orcid.org/0000-0002-0358-8298)
- Yufei Sun
- Yingwei Xue (ORCID: https://orcid.org/0000-0002-8427-9736)
- Ziyu Zhu (ORCID: https://orcid.org/0009-0005-0268-9563)
- Nan Wang (ORCID: https://orcid.org/0009-0001-3237-5339)
Institutions
- Harbin Medical University (CN)
- Third Affiliated Hospital of Harbin Medical University (CN)
Publication Details
- Journal
- World Journal of Gastroenterology
- Published
- 2024-10-16
- DOI
- https://doi.org/10.3748/wjg.v30.i40.4354
- Citations
- 4
- Primary Topic
- Gastric Cancer Management and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 1.68