AI Medical Compendium Topic

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Tooth, Deciduous

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[Effect of TNF-α on the ability of stem cells from human exfoliated deciduous teeth to promote osteoclastogenesis].

Shanghai kou qiang yi xue = Shanghai journal of stomatology
PURPOSE: To investigate the effect of tumor necrosis factor-α (TNF-α) on the ability of stem cells from human exfoliated deciduous teeth (SHED) to promote osteoclastogenesis.

Deep learning-based dental plaque detection on primary teeth: a comparison with clinical assessments.

BMC oral health
BACKGROUND: Dental plaque causes many common oral diseases (e.g., caries, gingivitis, and periodontitis). Therefore, plaque detection and control are extremely important for children's oral health. The objectives of this study were to design a deep l...

A pilot study of a deep learning approach to submerged primary tooth classification and detection.

International journal of computerized dentistry
AIM: The aim of the study was to compare the success and reliability of an artificial intelligence (AI) application in the detection and classification of submerged teeth in panoramic radiographs.

Artificial intelligence system for automatic deciduous tooth detection and numbering in panoramic radiographs.

Dento maxillo facial radiology
OBJECTIVE: This study evaluated the use of a deep-learning approach for automated detection and numbering of deciduous teeth in children as depicted on panoramic radiographs.

Effects of design software program and manufacturing method on the marginal and internal adaptation of esthetic crowns for primary teeth: A microcomputed tomography evaluation.

The Journal of prosthetic dentistry
STATEMENT OF PROBLEM: The adaptation of digitally produced crowns is affected by the design software program and manufacturing method. The effect of artificial intelligence (AI) software program design on the adaptation of the crowns is unclear and c...

Information fusion for infant age estimation from deciduous teeth using machine learning.

American journal of biological anthropology
OBJECTIVES: Over the past few years, several methods have been proposed to improve the accuracy of age estimation in infants with a focus on dental development as a reliable marker. However, traditional approaches have limitations in efficiently comb...

Machine learning aided single cell image analysis improves understanding of morphometric heterogeneity of human mesenchymal stem cells.

Methods (San Diego, Calif.)
The multipotent stem cells of our body have been largely harnessed in biotherapeutics. However, as they are derived from multiple anatomical sources, from different tissues, human mesenchymal stem cells (hMSCs) are a heterogeneous population showing ...

Novel AI-based tool for primary tooth segmentation on CBCT using convolutional neural networks: A validation study.

International journal of paediatric dentistry
BACKGROUND: Primary teeth segmentation on cone beam computed tomography (CBCT) scans is essential for paediatric treatment planning. Conventional methods, however, are time-consuming and necessitate advanced expertise.

Deep learning-based detection of irreversible pulpitis in primary molars.

International journal of paediatric dentistry
BACKGROUND: Changes in healthy and inflamed pulp on periapical radiographs are traditionally so subtle that they may be imperceptible to human experts, limiting its potential use as an adjunct clinical diagnostic feature.

Identifying Primary Proximal Caries Lesions in Pediatric Patients From Bitewing Radiographs Using Artificial Intelligence.

Pediatric dentistry
To develop a no-code artificial intelligence (AI) model capable of identifying primary proximal surface caries using bitewings among pediatric patients. One hundred bitewing radiographs acquired at pediatric dental clinics were anonymized and revie...