Predicting patient-reported outcomes following hip and knee replacement surgery using supervised machine learning

Predicting patient-reported outcomes following hip and knee replacement surgery using supervised machine learning

Abstract Background Machine-learning classifiers mostly offer good predictive performance and are increasingly used to support shared decision-making in clinical practice. Focusing on performance and practicability, this study evaluates prediction of patient-reported outcomes (PROs) by eight supervi...

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Bibliographic Details
Main Authors: Manuel Huber, Christoph Kurz, Reiner Leidl
Format: Article
Language:English
Published: BMC 2019-01-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Patient-reported outcomes
Hip replacement
Knee replacement
Shared decision-making
Machine learning
Binary classification
Online Access:http://link.springer.com/article/10.1186/s12911-018-0731-6

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http://link.springer.com/article/10.1186/s12911-018-0731-6

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