New approach for the diagnosis of extractions with neural network machine learning.

Journal: American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics

PMID: 26718386

Abstract

INTRODUCTION: The decision to extract teeth for orthodontic treatment is important and difficult because it tends to be based on the practitioner's experiences. The purposes of this study were to construct an artificial intelligence expert system for the diagnosis of extractions using neural network machine learning and to evaluate the performance of this model.

Authors

Seok-Ki Jung

Clinical instructor, Department of Orthodontics, Korea University Ansan Hospital, Ansan, Korea.
Tae-Woo Kim

Professor, Department of Orthodontics, School of Dentistry, Dental Research Institute, Seoul National University, Seoul, Korea. Electronic address: taewoo@snu.ac.kr.

Keywords

Adult Algorithms Anatomic Landmarks Artificial Intelligence Cephalometry Decision Making, Computer-Assisted Expert Systems Female Humans Incisor Lip Machine Learning Male Mandible Maxilla Nasal Bone Neural Networks, Computer Nose Orthodontics, Corrective Patient Care Planning Tooth Extraction Young Adult

External Resources

View on PubMed Access via DOI PubMed (26718386)

New approach for the diagnosis of extractions with neural network machine learning.

Abstract

Authors

Keywords

External Resources

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