Artificial intelligence-assisted machine learning models for predicting lung cancer survival
Large language model-ADA effectively facilitates the development of machine learning models for lung cancer survival prediction, enabling non-technical health care professionals to harness the power of advanced analytics. The findings underscore the importance of preoperative factors in predicting outcomes, while also highlighting the need for external validation across diverse settings.
Authors
- Yingchun Zeng (ORCID: https://orcid.org/0000-0001-9250-4086)
- Sicheng Hao (ORCID: https://orcid.org/0000-0002-8905-005X)
- Guolong Zhang (ORCID: https://orcid.org/0000-0003-4781-5816)
- Chen Huang (ORCID: https://orcid.org/0000-0002-8545-3679)
- Hongxia Xie
- Yue Yuan (ORCID: https://orcid.org/0000-0003-3980-0630)
- Yuqi Gu
- Wei Mi
Institutions
- National University of Singapore (SG)
- Hunan University (CN)
- Sir Run Run Shaw Hospital (CN)
- First Affiliated Hospital of Guangzhou Medical University (CN)
- Hangzhou City University
- Massachusetts Institute of Technology (US)
- Zhejiang University (CN)
- Guangzhou Medical University (CN)
Publication Details
- Journal
- Asia-Pacific Journal of Oncology Nursing
- Published
- 2025-03-07
- DOI
- https://doi.org/10.1016/j.apjon.2025.100680
- Citations
- 9
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 12.24