Concepedia

Evaluating the fairness and accuracy of machine learning–based predictions of clinical outcomes after anatomic and reverse total shoulder arthroplasty

Christine Allen, Vikas Kumar, Josie Elwell, Steven Overman, Bradley S. Schoch, William R. Aibinder, Moby Parsons, Jonathan P. Watling, Jia-Wei Kevin Ko, Bruno Gobbato,

Journal of Shoulder and Elbow Surgery · 2023 · 13 citations · 19 references

DOI

Concepts

References

19

Big Data's Disparate Impact

Solon Barocas, Andrew D. Selbst · SSRN Electronic Journal · 2016 · 2.1K citations · Full text

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Quantifying success after total shoulder arthroplasty: the minimal clinically important difference

Ryan W. Simovitch, Pierre-Henri Flurin, Thomas W. Wright et al. · Journal of Shoulder and Elbow Surgery · 2017 · 467 citations

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Can Machine Learning Algorithms Predict Which Patients Will Achieve Minimally Clinically Important Differences From Total Joint Arthroplasty?

Mark Alan Fontana, Stephen Lyman, Gourab K. Sarker et al. · Clinical Orthopaedics and Related Research · 2019 · 198 citations · Full text

, , +17

Quantifying success after total shoulder arthroplasty: the substantial clinical benefit

Ryan W. Simovitch, Pierre-Henri Flurin, Thomas W. Wright et al. · Journal of Shoulder and Elbow Surgery · 2018 · 185 citations

, , +13

Validation of a machine learning–derived clinical metric to quantify outcomes after total shoulder arthroplasty

Christopher Roche, Vikas Kumar, Steven Overman et al. · Journal of Shoulder and Elbow Surgery · 2021 · 102 citations

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