Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Ryan, Simovitch"'
Autor:
Bradley S. Schoch, Kevin Hao, Josie Elwell, Jennifer Traverse, Ryan Simovitch, Thomas Wright, Jospeh King
Publikováno v:
JSES International, Vol 8, Iss 6, Pp 1345- (2024)
Externí odkaz:
https://doaj.org/article/9147ddc6eba646b09c69666b1a6974a5
Autor:
Austin McCadden, Jared J. Reid, Bryce Kunkle, Venkatraman Kothandaraman, Kirsi S. Oldenburg, Alexander Greene, Bradley S. Schoch, Rick Papandrea, Ryan Simovitch, Thomas Wright, Moby Parsons, Pierre-Henri Flurin, Richard J. Friedman, Josef K. Eichinger
Publikováno v:
Seminars in Arthroplasty: JSES. 33:105-115
Autor:
Steven Overman, Vikas Kumar, Ankur Teredesai, Thomas W. Wright, Howard D. Routman, Ryan Simovitch, Christopher P. Roche, Joseph D. Zuckerman, Christine Allen, Pierre-Henri Flurin
Publikováno v:
Seminars in Arthroplasty: JSES. 32:226-237
Introduction We use machine learning to create predictive models from preoperative data to predict the Shoulder Arthroplasty Smart (SAS) score, the American Shoulder and Elbow Surgeons (ASES) score, and the Constant score at multiple postoperative ti
Autor:
Christopher P. Roche, Wen Fan, Ryan Simovitch, Thomas Wright, Pierre-Henri Flurin, Joseph D. Zuckerman, Howard Routman
Publikováno v:
Journal of Shoulder and Elbow Surgery.
Autor:
Steven Overman, Thomas W. Wright, Ankur Teredesai, Joseph D. Zuckerman, Christopher P. Roche, Vikas Kumar, Howard D. Routman, Ryan Simovitch, Pierre-Henri Flurin
Publikováno v:
Journal of Shoulder and Elbow Surgery. 30:2211-2224
Background We propose a new clinical assessment tool constructed using machine learning, called the Shoulder Arthroplasty Smart (SAS) score to quantify outcomes following total shoulder arthroplasty (TSA). Methods Clinical data from 3667 TSA patients
Autor:
Joseph D. Zuckerman, Ankur Teredesai, Howard D. Routman, Christopher P. Roche, Steven Overman, Vikas Kumar, Pierre-Henri Flurin, Thomas W. Wright, Ryan Simovitch
Publikováno v:
Seminars in Arthroplasty: JSES. 31:263-271
Background An important psychometric parameter of validity that is rarely assessed is predictive value. In this study we utilize machine learning to analyze the predictive value of 3 commonly used clinical measures to assess 2-year outcomes after tot
Autor:
Christopher P. Roche, Vikas Kumar, Ryan Simovitch, Howard D. Routman, Ankur Teredesai, Pierre-Henri Flurin, Joseph D. Zuckerman, Thomas W. Wright, Steven Overman
Publikováno v:
Journal of Shoulder and Elbow Surgery. 30:e225-e236
Background A machine learning analysis was conducted on 5774 shoulder arthroplasty patients to create predictive models for multiple clinical outcome measures after anatomic total shoulder arthroplasty (aTSA) and reverse total shoulder arthroplasty (
Autor:
Joseph D. Zuckerman, Ryan Simovitch, Thomas W. Wright, Howard D. Routman, Christopher P. Roche, Pierre-Henri Flurin
Publikováno v:
Journal of Bone and Joint Surgery. 102:1724-1733
This article was updated on TK because of a previous error, which was discovered after the preliminary version of the article was posted online. In Table VII, the fracture rate in the study by Walch et al. that had read "4.6% (21 of 457)" now reads "
Autor:
Joseph D. Zuckerman, Vikas Kumar, Steven Overman, Howard D. Routman, Thomas W. Wright, Ankur Teredesai, Ryan Simovitch, Christopher P. Roche, Pierre-Henri Flurin
Publikováno v:
Clin Orthop Relat Res
Background Machine learning techniques can identify complex relationships in large healthcare datasets and build prediction models that better inform physicians in ways that can assist in patient treatment decision-making. In the domain of shoulder a
Autor:
Joseph D. Zuckerman, Pierre-Henri Flurin, Thomas W. Wright, Christopher P. Roche, Ryan Simovitch
Publikováno v:
Journal of Shoulder and Elbow Surgery. 27:903-911
Background An understanding of the substantial clinical benefit (SCB) after total shoulder arthroplasty (TSA) may help to gauge a minimum threshold beyond which a patient perceives his or her outcome as being substantially better. This study quantifi