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Application and performance of artificial intelligence technology in forensic odontology - A systematic review
- Source :
- Legal medicine (Tokyo, Japan). 48
- Publication Year :
- 2020
-
Abstract
- Forensic odontology (FO) mainly deals with the identification of the individual through the remains, which mainly includes teeth and jawbones. Artificial intelligence (AI) technology has proven to be a breakthrough in providing reliable information in decision making in forensic sciences. This systematic review aimed to report on the application and performance of AI technology in FO. The data was gathered through searching for the articles in the renowned search engines, which have been published between January 2000 - June 2020. QUADAS-2 was adopted for the risk of bias analysis of the included studies. AI technology has been widely applied in FO for identifying bite-marks, predicting mandibular morphology, gender determination, and age estimation. Most of these AI models are based on either artificial neural networks (ANNs) or convolutional neural networks (CNNs). The results of the studies are promising. Studies have reported that these models display accuracy and precision equivalent to that of the trained examiners. These models can be promising tools when identifying victims of mass disasters and as an additive aid in medico-legal situations.
- Subjects :
- Male
Sex Determination Analysis
Computer science
Forensic dentistry
01 natural sciences
Convolutional neural network
Pathology and Forensic Medicine
Machine Learning
03 medical and health sciences
0302 clinical medicine
Deep Learning
Artificial Intelligence
Humans
Forensic odontology
030216 legal & forensic medicine
Artificial neural network
business.industry
Deep learning
010401 analytical chemistry
Mandibular morphology
0104 chemical sciences
Body Remains
Issues, ethics and legal aspects
Identification (information)
Age estimation
Female
Artificial intelligence
Neural Networks, Computer
Age Determination by Teeth
business
Forensic Dentistry
Subjects
Details
- ISSN :
- 18734162
- Volume :
- 48
- Database :
- OpenAIRE
- Journal :
- Legal medicine (Tokyo, Japan)
- Accession number :
- edsair.doi.dedup.....b01ca19d4116af0d52f82fd419b14ea1