Artificial Intelligence in Oral Health

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Artificial Intelligence in Oral Health

This Special Issue is intended to lay the foundation of AI applications focusing on oral health, including general dentistry, periodontology, implantology, oral surgery, oral radiology, orthodontics, and prosthodontics, among others.

Bibliographic Details
Other Authors:	Lee, Jae-Hong (Editor)
Format:	eBook
Language:	Inglés
Published:	Basel MDPI Books 2022
Subjects:	Medicine machine learning artificial intelligence malocclusion diagnostic imaging active learning maxillary sinusitis convolutional neural network deep learning segmentation oral microbiota LEfSe PCoA alloprevotella prevotella core microbiota artificial neural networks oral cancer diagnosis oral cancer prediction pit and fissure sealants caries assessment visual examination clinical evaluation convolutional neural networks transfer learning deep learning network YOLOv4 mandibular third molar inferior alveolar nerve contact relationship panoramic radiograph deep learning methods caries diagnosis dental panoramic images radiography Fourier transform infrared spectroscopy FTIR imaging spectral biomarker multivariate analysis discriminant model oral squamous cell carcinoma oral epithelial dysplasia oral potentially malignant disorder risk stratification early oral cancer detection dentigerous cysts histopathology images image classification odontogenic keratocysts radicular cysts AI screening diagnosis dentistry ultrasonography tongue algorithm dysphagia impacted tooth detection neural networks proximal caries training strategy small dataset periapical radiograph X-ray tooth extraction oroantral fistula operative planning
See on Biblioteca Universitat Ramon Llull:	https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009683468906719

Description
Summary:	This Special Issue is intended to lay the foundation of AI applications focusing on oral health, including general dentistry, periodontology, implantology, oral surgery, oral radiology, orthodontics, and prosthodontics, among others.
Physical Description:	1 electronic resource (190 p.)
Access:	Open access