Cita APA (7a ed.)
Digumarthi, V., Amin, T., Kanu, S., Mathew, J., Edwards, B., Peterson, L. A., . . . Hegarty, K. E. (2024). Preoperative prediction model for risk of readmission after total joint replacement surgery: A random forest approach leveraging NLP and unfairness mitigation for improved patient care and cost-effectiveness. Journal of Orthopaedic Surgery & Research, 19(1), 1-18.
Cita Chicago Style (17a ed.)
Digumarthi, Varun, Tapan Amin, Samuel Kanu, Joshua Mathew, Bryan Edwards, Lisa A. Peterson, Matthew E. Lundy, y Karen E. Hegarty. "Preoperative Prediction Model for Risk of Readmission After Total Joint Replacement Surgery: A Random Forest Approach Leveraging NLP and Unfairness Mitigation for Improved Patient Care and Cost-effectiveness." Journal of Orthopaedic Surgery & Research 19, no. 1 (2024): 1-18.
Cita MLA (9a ed.)
Digumarthi, Varun, et al. "Preoperative Prediction Model for Risk of Readmission After Total Joint Replacement Surgery: A Random Forest Approach Leveraging NLP and Unfairness Mitigation for Improved Patient Care and Cost-effectiveness." Journal of Orthopaedic Surgery & Research, vol. 19, no. 1, 2024, pp. 1-18.
Precaución: Estas citas no son 100% exactas.