Song X, Shi J, Zhu C, Xian F, Dong Z and Li J (2025) “XGBoost machine learning algorithm for predicting unplanned readmission in elderly patients with coronary heart disease.”, Geriatric nursing (New York, N.Y.), 66(Pt B), pp. 103609-103609. doi:10.1016/j.gerinurse.2025.103609.
Chicago Manual of Style 17th edition (full note)Song X, Shi J, Zhu C, Xian F, Dong Z, and Li J. “XGBoost Machine Learning Algorithm for Predicting Unplanned Readmission in Elderly Patients With Coronary Heart Disease.”. Geriatric Nursing (New York, N.Y.) 66, no. Pt B (November 1, 2025): 103609-9. https://doi.org/10.1016/j.gerinurse.2025.103609.
American Psychological Association 7th editionSong X, Shi J, Zhu C, Xian F, Dong Z, & Li J. (2025). XGBoost machine learning algorithm for predicting unplanned readmission in elderly patients with coronary heart disease. Geriatric Nursing (New York, N.Y.), 66(Pt B), 103609-103609. https://doi.org/10.1016/j.gerinurse.2025.103609
Modern Language Association 9th editionSong X, Shi J, Zhu C, Xian F, Dong Z, and Li J. “XGBoost Machine Learning Algorithm for Predicting Unplanned Readmission in Elderly Patients With Coronary Heart Disease.”. Geriatric Nursing (New York, N.Y.), vol. 66, no. Pt B, Nov. 2025, pp. 103609-, https://doi.org/10.1016/j.gerinurse.2025.103609.
ISO-690 (author-date, Deutsch)SONG X, SHI J, ZHU C, XIAN F, DONG Z and LI J, 2025. XGBoost machine learning algorithm for predicting unplanned readmission in elderly patients with coronary heart disease. Geriatric nursing (New York, N.Y.). 1 November 2025. vol. 66, no. Pt B, p. 103609-103609. DOI 10.1016/j.gerinurse.2025.103609