Implementation of machine learning models as a quantitative evaluation tool for preclinical studies in dental education.

Journal: Journal of dental education

PMID: 39327675

Abstract

PURPOSE AND OBJECTIVE: Objective, valid, and reliable evaluations are needed in order to develop haptic skills in dental education. The aim of this study is to investigate the validity and reliability of the machine learning method in evaluating the haptic skills of dentistry students.

Authors

Aybeniz Oguzhan

Department of Restorative Dentistry, Faculty of Dentistry, Ege University, Izmir, Turkey.
Cem Peskersoy

Department of Restorative Dentistry, Faculty of Dentistry, Ege University, Izmir, Turkey.
Elif Ercan Devrimci

Department of Restorative Dentistry, Faculty of Dentistry, Ege University, Izmir, Turkey.
Hande Kemaloglu

Department of Restorative Dentistry, Faculty of Dentistry, Ege University, Izmir, Turkey.
Tolga Kagan Onder

Department of Mechanical Engineering, ARQUQ Project Partnership, Izmir, Turkey.

Keywords

Clinical Competence Composite Resins Dental Amalgam Dental Restoration, Permanent Education, Dental Educational Measurement Humans Machine Learning Reproducibility of Results Students, Dental

External Resources

View on PubMed Access via DOI PubMed (39327675)

Implementation of machine learning models as a quantitative evaluation tool for preclinical studies in dental education.

Abstract

Authors

Keywords

External Resources

Popular Topics

Recent Journals