Interpretable Ensemble Learning Predicts Antibiotic Resistance in Treponema denticola Using Expert Classifiers

Interpretable Ensemble Learning Predicts Antibiotic Resistance in Treponema denticola Using Expert Classifiers

Introduction and Objectives: Antibiotic resistance is a global health concern, contributing to prolonged hospital stays, increased medical costs, and higher mortality rates. Addressing antimicrobial resistance (AMR) in periodontal infections requires targeted therapies and a multifaceted approach. T...

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Bibliographic Details
Main Authors: Pradeep Kumar Yadalam, Prabhu Manickam Natarajan, Carlos M. Ardila
Format: Article
Language:English
Published: Elsevier 2025-10-01
Series:International Dental Journal
Subjects:
Periodontitis
Machine learning
Antimicrobial resistance
Treponema denticola
Microorganisms
Online Access:http://www.sciencedirect.com/science/article/pii/S002065392500173X
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http://www.sciencedirect.com/science/article/pii/S002065392500173X

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