An artificial neural network approach for rational decision-making in borderline orthodontic cases: A preliminary analytical observational in silico study.

INTRODUCTION: Artificial intelligence (AI) technology has transformed the way healthcare functions in the present scenario. In orthodontics, expert systems and machine learning have aided clinicians in making complex, multifactorial decisions. One such scenario is an extraction decision in a borderline case. OBJECTIVE: The present in silico study was planned with the intention of building an AI model for extraction decisions in borderline orthodontic cases. DESIGN: An observational analytical study. SETTING: Department of Orthodontics, Hitkarini Dental College and Hospital, Madhya Pradesh Medical University, Jabalpur, India. METHODS: An artificial neural network (ANN) model for extraction or non-extraction decisions in borderline orthodontic cases was constructed based on a supervised learning algorithm using the Python (version 3.9) Sci-Kit Learn library and feed-forward backpropagation method. Based on 40 borderline orthodontic cases, 20 experienced clinicians were asked to recommend extraction or non-extraction treatment. The decision of the orthodontist and the diagnostic records, including the selected extraoral and intra-oral features, model analysis and cephalometric analysis parameters, constituted the training dataset of AI. The built-in model was then tested using a testing dataset of 20 borderline cases. After running the model on the testing dataset, the accuracy, F1 score, precision and recall were calculated. RESULTS: The present AI model showed an accuracy of 97.97% for extraction and non-extraction decision-making. The receiver operating curve (ROC) and cumulative accuracy profile showed a near-perfect model with precision, recall and F1 values of 0.80, 0.84 and 0.82 for non-extraction decisions and 0.90, 0.87 and 0.88 for extraction decisions. LIMITATION: As the present study was preliminary in nature, the dataset included was too small and population-specific. CONCLUSION: The present AI model gave accurate results in decision-making capabilities related to extraction and non-extraction treatment modalities in borderline orthodontic cases of the present population.

Evaluation of stresses and displacement in the craniofacial region as a reaction to bone-anchored maxillary protraction in conjugation with posterior bite plane and rapid maxillary expansion in patients with Class III malocclusion: A finite element analysis study.

INTRODUCTION: Treating a Class III malocclusion is often challenging for orthodontists. Bone-anchored maxillary protraction (BAMP) is known for achieving a significant maxillary protraction. The study aimed to evaluate the stress distribution and displacement of craniofacial bones as a reaction to the forces of BAMP, along with rapid maxillary expander and the posterior bite plane, in growing patients with skeletal Class III malocclusion using a finite element method. METHODS: An finite element model was constructed from the spiral computed tomographic images of a skull from an 11-year-old growing patient with skeletal Class III malocclusion along with BAMP, rapid maxillary expander, and the posterior bite plane. The created model had 105,189 nodes and 481,066 elements. After assigning the appropriate material properties and the boundary condition, 800 g of transverse force per side and a Class III intraoral elastic 250 g of force per side were applied to the model, and after the postprocessing, the results were obtained in the form of color bands. RESULTS: The maxilla and the attached structures were displaced and expanded transversely. The maxilla was displaced anteriorly by 0.692 mm, and the mandible was displaced backward by 0.204 mm in the sagittal direction. The anterior region of the maxilla and mandible, dentition, and nasal bone were rotated counterclockwise. Displacement in an upward direction was greatest at the symphysis region of the mandible. The stresses experienced by most of the bones were tensile, with the maxilla and maxillary dentition experiencing the maximum. CONCLUSIONS: Favorable changes were appreciated with maxillary forward and mandibular backward displacement, with appreciable tensile stresses in all the bones.