APA (7th ed.) Citation

HJ, C., C, L., JS, L., YJ, O., JS, C., JH, J., . . . SJ, O. (2026). Time-to-event ensemble machine learning approach for predicting long-term survival of abdominal aortic aneurysm patients undergoing endovascular aneurysm repair. PloS one, 21(6), e0349122. https://doi.org/10.1371/journal.pone.0349122

Chicago Style (17th ed.) Citation

HJ, Choi, Lee C, Lim JS, Ok YJ, Choi JS, Jeong JH, Seong YW, Moon HJ, and Oh SJ. "Time-to-event Ensemble Machine Learning Approach for Predicting Long-term Survival of Abdominal Aortic Aneurysm Patients Undergoing Endovascular Aneurysm Repair." PloS One 21, no. 6 (2026): e0349122. https://doi.org/10.1371/journal.pone.0349122.

MLA (9th ed.) Citation

HJ, Choi, et al. "Time-to-event Ensemble Machine Learning Approach for Predicting Long-term Survival of Abdominal Aortic Aneurysm Patients Undergoing Endovascular Aneurysm Repair." PloS One, vol. 21, no. 6, 2026, p. e0349122, https://doi.org/10.1371/journal.pone.0349122.