APA (7th ed.) Citation

Geitenbeek, R., Baltus, S. C., Broekman, M., Barendsen, S. N., Frieben, M. C., Asaggau, I., . . . Consten, E. C. J. (2025). Multi-modal machine learning for evaluating the predictive value of pelvimetric measurements (pelvimetry) for anastomotic leakage after restorative low anterior resection. Cancers, 17(6), . https://doi.org/10.3390/cancers17061051

Chicago Style (17th ed.) Citation

Geitenbeek, Ritch, et al. "Multi-modal Machine Learning for Evaluating the Predictive Value of Pelvimetric Measurements (pelvimetry) for Anastomotic Leakage After Restorative Low Anterior Resection." Cancers 17, no. 6 (2025). https://doi.org/10.3390/cancers17061051.

MLA (9th ed.) Citation

Geitenbeek, Ritch, et al. "Multi-modal Machine Learning for Evaluating the Predictive Value of Pelvimetric Measurements (pelvimetry) for Anastomotic Leakage After Restorative Low Anterior Resection." Cancers, vol. 17, no. 6, 2025, https://doi.org/10.3390/cancers17061051.