Predicting Chemotherapy Response in Patients With Advanced or Metastatic Pancreatic Cancer Using Machine Learning
ML models trained on multicenter data can effectively predict early mortality risk and help personalize chemotherapy selection in advanced or metastatic pancreatic cancer, potentially improving clinical outcomes.
Authors
- Jaekyung Cheon (ORCID: https://orcid.org/0000-0001-8439-1739)
- George Courcoubetis (ORCID: https://orcid.org/0000-0001-8622-6251)
- Kyu‐pyo Kim (ORCID: https://orcid.org/0000-0001-7848-5923)
- Baek‐Yeol Ryoo (ORCID: https://orcid.org/0000-0002-9052-833X)
- Seung-yeon Lim (ORCID: https://orcid.org/0000-0001-8295-3072)
- Jamin Koo (ORCID: https://orcid.org/0000-0003-4299-1546)
- Gyucheol Choi (ORCID: https://orcid.org/0000-0002-1479-6236)
- Moonho Kim (ORCID: https://orcid.org/0000-0002-1777-3267)
- Changhoon Yoo (ORCID: https://orcid.org/0000-0002-1451-8455)
- Ho-Suk Oh
- Heung-Moon Chang
Institutions
- Ulsan College (KR)
- Asan Medical Center (KR)
- University of Ulsan (KR)
- Mountain View Clinical Research (US)
- Gangneung Asan Hospital (KR)
- Korea Economic Research Institute (KR)
- Hongik University (KR)
Publication Details
- Journal
- JCO Clinical Cancer Informatics
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1200/cci-25-00124
- Primary Topic
- Pancreatic and Hepatic Oncology Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00