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Using a machine learning system to forecast how satisfied patients with temporomandibular joint disease would be with their treatment outcomes
Abstract
Temporomandibular joint disorders are distinguished by a diverse set of clinical symptoms that have a significant influence on a patient's quality of life. The consistency of a patient's subjective appraisal of his condition with objective clinical manifestations is critical to the therapy outcome. We previously devised an algorithm for predicting patient satisfaction with the outcomes of interdisciplinary rehabilitation. As part of this study, we demonstrated the feasibility of employing this method in clinical practice in patients with temporomandibular joint disease using two clinical instances.
About the Authors
N. A. Byzov
ФГБУ НМИЦ «ЦНИИС и ЧЛХ» Минздрава России
Russian Federation
Russian Federation
I. V. Gunenkova
ФГБУ НМИЦ «ЦНИИС и ЧЛХ» Минздрава России
Russian Federation
Russian Federation
D. A. Volcheck
ФГБУ НМИЦ «ЦНИИС и ЧЛХ» Минздрава России
Russian Federation
Russian Federation
A. M. Dybov
ФГБУ ДПО «ЦГМА»
Belarus
Belarus
G. B. Ospanova
ФГБУ НМИЦ «ЦНИИС и ЧЛХ» Минздрава России
Russian Federation
Russian Federation
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Review
For citations:
Byzov N.A., Gunenkova I.V., Volcheck D.A., Dybov A.M., Ospanova G.B. Using a machine learning system to forecast how satisfied patients with temporomandibular joint disease would be with their treatment outcomes. Orthodontia. 2024;(2):39-43. (In Russ.)
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