Tannor Court
Papers
1
Total Citations
16
H-Index
1
About
Dr. Tannor Court is a rising figure in orthopedic research, with a focused expertise in leveraging computational methods to improve surgical outcomes. His work centers on the application of machine learning to predictive analytics in arthroplasty, aiming to enhance patient safety and optimize perioperative care. His most cited study, "Predicting Factors for Blood Transfusion in Primary Total Knee Arthroplasty Using a Machine Learning Method" (2023, 16 citations), represents a significant contribution to the field. In this work, Dr. Court developed novel machine learning models to identify key predictors of allogeneic blood transfusion following total knee arthroplasty (TKA), a common and serious postoperative complication. By moving beyond traditional statistical analysis, his research provides clinicians with a more accurate, data-driven tool for risk stratification, enabling proactive management of acute blood loss anemia. This innovative approach not only highlights the potential of artificial intelligence in orthopedics but also directly addresses a critical gap in patient safety. Dr. Court’s work is paving the way for more personalized, predictive surgical care, marking him as a researcher to watch in the evolving landscape of data-driven medicine.
Research Focus
Key Achievements
Top Papers
- 1