Machine Learning–Based Radiomics for Differentiating Pancreatic Lesions: A Potential Tool to Enhance Clinical Decision‐Making and Nursing Management
Radiomics-based ML models effectively differentiated benign, borderline, and malignant pancreatic tumors. The nomogram combining radiomic features with CA19-9 demonstrated robust performance, showing considerable potential to streamline the diagnostic process and facilitate timely care planning for patients with suspected pancreatic cancer.
Authors
- Siwei Wang (ORCID: https://orcid.org/0009-0003-8998-4551)
- Xiaoxuan Li (ORCID: https://orcid.org/0009-0006-7419-433X)
- J. Liu (ORCID: https://orcid.org/0009-0002-7225-589X)
- Jing Guo (ORCID: https://orcid.org/0000-0002-6077-5188)
- Xiaomin Xing (ORCID: https://orcid.org/0000-0002-0642-3122)
- Jinzhao Cui (ORCID: https://orcid.org/0009-0007-5095-3722)
- Xinchi Luan
Institutions
- Qingdao University (CN)
- Affiliated Hospital of Qingdao University (CN)
Publication Details
- Journal
- Journal of Nursing Management
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1155/jonm/8038903
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Natural Science Foundation of Shandong Province