Accuracy of Linear Measurements of Maxillary Sinus Dimensions in Gender Identification Using Machine Learning

被引：0

作者：

Al-Amodi, Abdullah ^{[1
]}

Kamel, Ibrahim ^{[1
]}

Al-Rawi, Natheer H. ^{[2
]}

Uthman, AsmaaT ^{[3
]}

Shetty, Shishir ^{[2
]}

机构：

[1] Univ Sharjah, Coll Comp Informat, Sharjah, U Arab Emirates

[2] Univ Sharjah, Coll Dent Med, Sharjah, U Arab Emirates

[3] Gulf Med Univ, Coll Dent, Ajman, U Arab Emirates

来源：

2021 14TH INTERNATIONAL CONFERENCE ON DEVELOPMENTS IN ESYSTEMS ENGINEERING (DESE) | 2021年

关键词：

Artificial intelligence; maxillary sinus; forensic medicine; gender identification; MULTIDETECTOR COMPUTED-TOMOGRAPHY;

D O I：

10.1109/DESE54285.2021.9719421

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Linear measurements of the maxillary sinus are useful for gender prediction. This variation could be used for forensic identification purposes in mass disasters. The study aims to evaluate the accuracy of the artificial intelligence-based technique in gender prediction using linear measurements of maxillary sinus from Cone Beam Computed Tomography CBCT scans.

引用

页码：407 / 412

页数：6

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