Brian Forsythe to Machine Learning
This is a "connection" page, showing publications Brian Forsythe has written about Machine Learning.
Connection Strength
1.040
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Editorial Commentary: Machine Learning and Artificial Intelligence Are Tools Requiring Physician and Patient Input When Screening Patients at Risk for Extended, Postoperative Opioid Use. Arthroscopy. 2023 06; 39(6):1512-1514.
Score: 0.210
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Implementation of Machine Learning to Predict Cost of Care Associated with Ambulatory Single-Level Lumbar Decompression. World Neurosurg. 2022 Nov; 167:e1072-e1079.
Score: 0.200
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Duration of Care and Operative Time Are the Primary Drivers of Total Charges After Ambulatory Hip Arthroscopy: A Machine Learning Analysis. Arthroscopy. 2022 07; 38(7):2204-2216.e3.
Score: 0.190
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Machine-learning model successfully predicts patients at risk for prolonged postoperative opioid use following elective knee arthroscopy. Knee Surg Sports Traumatol Arthrosc. 2022 Mar; 30(3):762-772.
Score: 0.178
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Machine learning can reliably identify patients at risk of overnight hospital admission following anterior cruciate ligament reconstruction. Knee Surg Sports Traumatol Arthrosc. 2021 Sep; 29(9):2958-2966.
Score: 0.175
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Development of a Machine Learning Algorithm to Predict Nonroutine Discharge Following Unicompartmental Knee Arthroplasty. J Arthroplasty. 2021 05; 36(5):1568-1576.
Score: 0.044
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Development of supervised machine learning algorithms for prediction of satisfaction at 2 years following total shoulder arthroplasty. J Shoulder Elbow Surg. 2021 Jun; 30(6):e290-e299.
Score: 0.044