Prediction of 30-Day Hospital Readmissions for All-Cause Dental Conditions using Machine Learning

Man Hung1 Roseman University of Health Sciences, College of Dental Medicine, South Jordan, UT, USA;2 University of Utah, Department of Family and Preventive Medicine, Salt Lake City, UT, USA;3 University of Utah, Department of Orthopaedics, Salt Lake City, UT, USA;4 University of Utah, School of Business, Salt Lake City, UT, USA;5 George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USACorrespondence[email protected]

https://orcid.org/0000-0003-2827-3740

Wei Li2 University of Utah, Department of Family and Preventive Medicine, Salt Lake City, UT, USA

Eric S Hon6 University of Chicago, Department of Economics, Chicago, IL, USA

Sharon Su1 Roseman University of Health Sciences, College of Dental Medicine, South Jordan, UT, USA

Weicong Su7 University of Utah, Department of Mathematics, Salt Lake City, UT, USA

Yao He8 University of Utah Alzheimer’s Center, Salt Lake City, UT, USA

Xiaoming Sheng9 University of Utah, College of Nursing, Salt Lake City, UT, USA

Richard Holubkov10 University of Utah, Department of Pediatrics, Salt Lake City, UT, USA

Martin S Lipsky1 Roseman University of Health Sciences, College of Dental Medicine, South Jordan, UT, USA

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Prediction of 30-Day Hospital Readmissions for All-Cause Dental Conditions using Machine Learning

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Prediction of 30-Day Hospital Readmissions for All-Cause Dental Conditions using Machine Learning

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