Using machine learning to identify risk factors for pancreatic cancer: a retrospective cohort study of real-world data
Machine learning algorithms confirmed that KRAS gene mutation, hyperlipidaemia, and pancreatitis are potential risk factors for pancreatic cancer. Additionally, the coexistence of KRAS gene mutation and pancreatitis, as well as KRAS gene mutation and pancreatic cysts, is associated with an increased risk of pancreatic cancer. Our findings offered valuable implications for public health strategies targeting the prevention and early detection of pancreatic cancer.
Authors
- Chunqi Liu
- Yimei Huang (ORCID: https://orcid.org/0000-0002-2011-4844)
- Yinglan Zhao (ORCID: https://orcid.org/0000-0002-5168-5842)
- Rui Tang (ORCID: https://orcid.org/0000-0002-6950-9580)
- Yice Zhang
- Biao Zhu (ORCID: https://orcid.org/0000-0002-5041-9630)
- Yuzhou Xiao (ORCID: https://orcid.org/0000-0001-8934-4448)
- Na Su (ORCID: https://orcid.org/0000-0001-6466-1797)
- Ni Jiang
Institutions
- UF Health Shands Hospital (US)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Sichuan University (CN)
- University of Florida Health (US)
- West China Hospital of Sichuan University (CN)
- State Key Laboratory of Biotherapy
- University of Florida Health Science Center (US)
Publication Details
- Journal
- Frontiers in Pharmacology
- Published
- 2024-11-21
- DOI
- https://doi.org/10.3389/fphar.2024.1510220
- Citations
- 4
- Primary Topic
- Pancreatic and Hepatic Oncology Research
- Type
- article
- Field-Weighted Citation Impact
- 1.13
Funders
- Sichuan University
- Sichuan Province Science and Technology Support Program
- West China Hospital, Sichuan University