Applying machine learning to construct an association model for lung cancer and environmental hormone high-risk factors and nursing assessment reconstruction.

The model was built from a company-administered biological database, and the paper does not report funding or conflicts beyond authorized access. The database analysis used 689 samples from patients aged 5 to 90 years, and the paper does not describe a separate comparison group of people without lung cancer. The clinical validation included only 128 patients with lung adenocarcinoma, recruited by convenience sampling from specialized cancer hospitals, and 91.4% lived in northern Taiwan, so it cannot show how the model performs in other patients or settings. The paper reports different model performance values in different sections, including logistic regression AUC 0.720 in the database comparison and AUC 0.893 in clinical validation. The nursing assessment suggestions are proposals from the authors; the study did not test whether adding these questions improves patient care or outcomes.

No explicit funding or conflict-of-interest statement is included. The paper states that access to the biological database was authorized by FUGA Biotechnology Co., Ltd., which administered the database.

Do not conclude that avoiding these foods or exposures will lower lung cancer risk or that cadmium causes lung cancer. The study reports associations and model performance, not a tested intervention, and the validation sample had only lung adenocarcinoma patients without a comparison group.