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Related Experiment Video

Updated: May 23, 2026

The Establishment of a Murine Mandibular Molar Extraction Socket Healing Model
04:19

The Establishment of a Murine Mandibular Molar Extraction Socket Healing Model

Published on: January 13, 2023

Machine learning-based approach for predicting the extraction time of a mandibular third molar.

Atsushi Danjo1, Motoki Fukuda2, Reona Aijima1

  • 1Department of Oral and Maxillofacial Surgery, Faculty of Medicine, Saga University, Saga, Japan.

Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology
|May 21, 2026
PubMed
Summary

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Predicting mandibular third molar extraction time is complex. A machine learning model using surgeon experience and radiographic features accurately predicted surgery duration at specific time thresholds.

Area of Science:

  • Oral and Maxillofacial Surgery
  • Machine Learning in Healthcare
  • Surgical Outcomes Prediction

Background:

  • Predicting surgical duration for mandibular third molar extraction is difficult due to complex interactions between patient, tooth, and operator factors.
  • Accurate time prediction is crucial for surgical planning and resource management.

Purpose of the Study:

  • To develop an interpretable machine learning model for predicting mandibular third molar extraction surgical time.
  • To identify key predictors of surgical duration using patient demographics, radiographic features, and surgeon variables.

Main Methods:

  • Retrospective review of 713 mandibular third molar extractions.
  • Development of machine learning models using a no-code platform (Prediction One).
  • Reframing prediction as binary classification at clinically relevant time thresholds (≥31, ≥46, ≥61 minutes) and benchmarking against traditional models.

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Using Inducible Osteoblastic Lineage-Specific Stat3 Knockout Mice to Study Alveolar Bone Remodeling During Orthodontic Tooth Movement

Published on: July 21, 2023

Related Experiment Videos

Last Updated: May 23, 2026

The Establishment of a Murine Mandibular Molar Extraction Socket Healing Model
04:19

The Establishment of a Murine Mandibular Molar Extraction Socket Healing Model

Published on: January 13, 2023

Using Inducible Osteoblastic Lineage-Specific Stat3 Knockout Mice to Study Alveolar Bone Remodeling During Orthodontic Tooth Movement
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Using Inducible Osteoblastic Lineage-Specific Stat3 Knockout Mice to Study Alveolar Bone Remodeling During Orthodontic Tooth Movement

Published on: July 21, 2023

Main Results:

  • The model predicting durations ≥31 minutes achieved the best performance (accuracy 0.75, AUC 0.80), outperforming comparator models.
  • Surgeon experience and specialist certification were the most significant predictors of surgical time.
  • Root-related radiographic morphology was also a strong contributor, while Pell and Gregory classification showed limited predictive value.

Conclusions:

  • Threshold-based prediction of mandibular third molar extraction time is feasible and more effective than continuous-time prediction.
  • Surgeon experience and specific radiographic features are key determinants of surgical duration.
  • The study identified factors with substantial and minimal impact on predicting surgical time, aiding in clinical practice.