Application of a Multi-Layer Perceptron in Preoperative Screening for Orthognathic Surgery.

IF 2.3 Q3 MEDICAL INFORMATICS
Natkritta Chaiprasittikul, Bhornsawan Thanathornwong, Suchaya Pornprasertsuk-Damrongsri, Somchart Raocharernporn, Somporn Maponthong, Somchai Manopatanakul
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引用次数: 1

Abstract

Objectives: Orthognathic surgery is used to treat moderate to severe occlusal discrepancies. Examinations and measurements for preoperative screening are essential procedures. A careful analysis is needed to decide whether cases require orthognathic surgery. This study developed screening software using a multi-layer perceptron to determine whether orthognathic surgery is required.

Methods: In total, 538 digital lateral cephalometric radiographs were retrospectively collected from a hospital data system. The input data consisted of seven cephalometric variables. All cephalograms were analyzed by the Detectron2 detection and segmentation algorithms. A keypoint region-based convolutional neural network (R-CNN) was used for object detection, and an artificial neural network (ANN) was used for classification. This novel neural network decision support system was created and validated using Keras software. The output data are shown as a number from 0 to 1, with cases requiring orthognathic surgery being indicated by a number approaching 1.

Results: The screening software demonstrated a diagnostic agreement of 96.3% with specialists regarding the requirement for orthognathic surgery. A confusion matrix showed that only 2 out of 54 cases were misdiagnosed (accuracy = 0.963, sensitivity = 1, precision = 0.93, F-value = 0.963, area under the curve = 0.96).

Conclusions: Orthognathic surgery screening with a keypoint R-CNN for object detection and an ANN for classification showed 96.3% diagnostic agreement in this study.

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多层感知器在正颌手术术前筛查中的应用。
目的:正颌手术用于治疗中重度咬合差异。术前筛查的检查和测量是必不可少的程序。需要仔细分析以决定病例是否需要进行正颌手术。本研究开发了使用多层感知器的筛选软件,以确定是否需要进行正颌手术。方法:从医院数据系统中回顾性收集538张数字侧位头颅x线片。输入数据包括7个头位测量变量。采用Detectron2检测和分割算法对所有脑图进行分析。使用基于关键点区域的卷积神经网络(R-CNN)进行目标检测,使用人工神经网络(ANN)进行分类。利用Keras软件建立并验证了该神经网络决策支持系统。输出数据显示为0到1之间的数字,需要进行正颌手术的病例用接近1的数字表示。结果:筛选软件与专家对正颌手术的诊断符合率为96.3%。混淆矩阵显示,54例中仅有2例误诊(准确度= 0.963,灵敏度= 1,精密度= 0.93,f值= 0.963,曲线下面积= 0.96)。结论:本研究正颌手术筛查采用关键点R-CNN进行目标检测,ANN进行分类,诊断符合率为96.3%。
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来源期刊
Healthcare Informatics Research
Healthcare Informatics Research MEDICAL INFORMATICS-
CiteScore
4.90
自引率
6.90%
发文量
44
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