Chirongoma, T., Cabrera, A., Bouterse, A., Chung, D., Patton, D., & Essilfie, A. (2024). Predicting Prolonged Length of Hospital Stay and Identifying Risk Factors Following Total Ankle Arthroplasty: A Supervised Machine Learning Methodology. Journal of Foot & Ankle Surgery, 63(5), 557-562.
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Cita Chicago Style (17a ed.)
Chirongoma, Tadiwanashe, Andrew Cabrera, Alexander Bouterse, David Chung, Daniel Patton, y Anthony Essilfie. "Predicting Prolonged Length of Hospital Stay and Identifying Risk Factors Following Total Ankle Arthroplasty: A Supervised Machine Learning Methodology."
Journal of Foot & Ankle Surgery 63, no. 5 (2024): 557-562.
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Cita MLA (9a ed.)
Chirongoma, Tadiwanashe, et al. "Predicting Prolonged Length of Hospital Stay and Identifying Risk Factors Following Total Ankle Arthroplasty: A Supervised Machine Learning Methodology."
Journal of Foot & Ankle Surgery, vol. 63, no. 5, 2024, pp. 557-562.
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