Cortical bone thickness in different sagittal skeletal relationship: assessment and predictive modelling using artificial neural network / Nagham Mohammed Abdullah Al-Jaf

Introduction: Miniscrews as anchorage devices are being increasingly used by orthodontists. Cortical thickness is a major factor affecting the success of miniscrew placement. Orthodontists treat patients with different sagittal skeletal relations. Some clinicians use three-dimensional imaging for as...

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Main Author:	Abdullah Al-Jaf, Nagham Mohammed
Format:	Thesis
Language:	English
Published:	2019
Subjects:	Back propagation (Artificial intelligence) Neural networks (Computer science)
Online Access:	https://ir.uitm.edu.my/id/eprint/82833/1/82833.pdf
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id	my-uitm-ir.82833
record_format	uketd_dc
spelling	my-uitm-ir.828332024-02-02T03:00:52Z Cortical bone thickness in different sagittal skeletal relationship: assessment and predictive modelling using artificial neural network / Nagham Mohammed Abdullah Al-Jaf 2019 Abdullah Al-Jaf, Nagham Mohammed Back propagation (Artificial intelligence) Neural networks (Computer science) Introduction: Miniscrews as anchorage devices are being increasingly used by orthodontists. Cortical thickness is a major factor affecting the success of miniscrew placement. Orthodontists treat patients with different sagittal skeletal relations. Some clinicians use three-dimensional imaging for assessment of cortical thickness for miniscrew placement. Objectives: To assess buccal cortical thickness, interradicular distance and palatal cortical thickness in different sagittal skeletal relationship. The other objective of this study was to formulate a prediction model for buccal cortical thickness without exposing patients to three-dimensional imaging and high radiation dose. Methods: Archived cone beam computed tomography (CBCT) scans of 240 adult subjects with Class I, II and III sagittal skeletal relationship and normal vertical relation were used. The scans were divided into three groups of 80 subjects with equal gender distribution. Buccal cortical thickness and interradicular distance were measured in the alveolar processes of the maxilla and mandible. The sites measured were from between central incisors to the site between the two molars. Palatal cortical thickness was also measured at nine locations. Analysis of variance (ANOVA) with post-hoc Tukey test was used with a significance level of p < 0.05 to detect differences between sagittal skeletal classes. 2019 Thesis https://ir.uitm.edu.my/id/eprint/82833/ https://ir.uitm.edu.my/id/eprint/82833/1/82833.pdf text en public phd doctoral Universiti Teknologi MARA (UiTM) Faculty of Dentistry Abu Hassan, Mohamed Ibrahim
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Abu Hassan, Mohamed Ibrahim
topic	Back propagation (Artificial intelligence) Neural networks (Computer science)
spellingShingle	Back propagation (Artificial intelligence) Neural networks (Computer science) Abdullah Al-Jaf, Nagham Mohammed Cortical bone thickness in different sagittal skeletal relationship: assessment and predictive modelling using artificial neural network / Nagham Mohammed Abdullah Al-Jaf
description	Introduction: Miniscrews as anchorage devices are being increasingly used by orthodontists. Cortical thickness is a major factor affecting the success of miniscrew placement. Orthodontists treat patients with different sagittal skeletal relations. Some clinicians use three-dimensional imaging for assessment of cortical thickness for miniscrew placement. Objectives: To assess buccal cortical thickness, interradicular distance and palatal cortical thickness in different sagittal skeletal relationship. The other objective of this study was to formulate a prediction model for buccal cortical thickness without exposing patients to three-dimensional imaging and high radiation dose. Methods: Archived cone beam computed tomography (CBCT) scans of 240 adult subjects with Class I, II and III sagittal skeletal relationship and normal vertical relation were used. The scans were divided into three groups of 80 subjects with equal gender distribution. Buccal cortical thickness and interradicular distance were measured in the alveolar processes of the maxilla and mandible. The sites measured were from between central incisors to the site between the two molars. Palatal cortical thickness was also measured at nine locations. Analysis of variance (ANOVA) with post-hoc Tukey test was used with a significance level of p < 0.05 to detect differences between sagittal skeletal classes.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Abdullah Al-Jaf, Nagham Mohammed
author_facet	Abdullah Al-Jaf, Nagham Mohammed
author_sort	Abdullah Al-Jaf, Nagham Mohammed
title	Cortical bone thickness in different sagittal skeletal relationship: assessment and predictive modelling using artificial neural network / Nagham Mohammed Abdullah Al-Jaf
title_short	Cortical bone thickness in different sagittal skeletal relationship: assessment and predictive modelling using artificial neural network / Nagham Mohammed Abdullah Al-Jaf
title_full	Cortical bone thickness in different sagittal skeletal relationship: assessment and predictive modelling using artificial neural network / Nagham Mohammed Abdullah Al-Jaf
title_fullStr	Cortical bone thickness in different sagittal skeletal relationship: assessment and predictive modelling using artificial neural network / Nagham Mohammed Abdullah Al-Jaf
title_full_unstemmed	Cortical bone thickness in different sagittal skeletal relationship: assessment and predictive modelling using artificial neural network / Nagham Mohammed Abdullah Al-Jaf
title_sort	cortical bone thickness in different sagittal skeletal relationship: assessment and predictive modelling using artificial neural network / nagham mohammed abdullah al-jaf
granting_institution	Universiti Teknologi MARA (UiTM)
granting_department	Faculty of Dentistry
publishDate	2019
url	https://ir.uitm.edu.my/id/eprint/82833/1/82833.pdf
_version_	1794191949121454080

Cortical bone thickness in different sagittal skeletal relationship: assessment and predictive modelling using artificial neural network / Nagham Mohammed Abdullah Al-Jaf

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