Machine learning models for prognosis prediction in regenerative endodontic procedures

Machine learning models for prognosis prediction in regenerative endodontic procedures

Abstract Background This study aimed to establish and validate machine learning (ML) models to predict the prognosis of regenerative endodontic procedures (REPs) clinically, assisting clinicians in decision-making and avoiding treatment failure. Methods A total of 198 patients with 268 teeth were in...

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Bibliographic Details
Main Authors: Jing Lu, Qianqian Cai, Kaizhi Chen, Bill Kahler, Jun Yao, Yanjun Zhang, Dali Zheng, Youguang Lu
Format: Article
Language:English
Published: BMC 2025-02-01
Series:BMC Oral Health
Subjects:
Machine learning
Prognosis prediction
Regenerative endodontic procedures
Online Access:https://doi.org/10.1186/s12903-025-05531-3
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https://doi.org/10.1186/s12903-025-05531-3

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