Comparison of the Predicting Performance for Fate of Medial Meniscus Posterior Root Tear Based on Treatment Strategies: A Comparison between Logistic Regression, Gradient Boosting, and CNN Algorithms

Comparison of the Predicting Performance for Fate of Medial Meniscus Posterior Root Tear Based on Treatment Strategies: A Comparison between Logistic Regression, Gradient Boosting, and CNN Algorithms

This study aimed to validate the accuracy and prediction performance of machine learning (ML), deep learning (DL), and logistic regression methods in the treatment of medial meniscus posterior root tears (MMPRT). From July 2003 to May 2018, 640 patients diagnosed with MMPRT were included. First, the...

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Bibliographic Details
Main Authors: Jae-Ik Lee, Dong-Hyun Kim, Hyun-Jin Yoo, Han-Gyeol Choi, Yong-Seuk Lee
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Diagnostics
Subjects:
knee
medial meniscus root tear
affecting factors
artificial intelligence
predicting performance
Online Access:https://www.mdpi.com/2075-4418/11/7/1225

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