Dental Health

Deep learning for 3D cephalometric landmarking with heterogeneous multi-center CBCT dataset.

Cephalometric analysis is critically important and common procedure prior to orthodontic treatment and orthognathic surgery. Recently, deep learning approaches have been proposed for automatic 3D cephalometric analysis based on landmarking from CBCT scans. However, these approaches have relied on uniform datasets from a single center or imaging device but without considering patient ethnicity. In ...

Estimating mandibular growth stage based on cervical vertebral maturation in lateral cephalometric radiographs using artificial intelligence.

INTRODUCTION: Determining the right time for orthodontic treatment is one of the most important factors affecting the treatment plan and its outcome. The aim of this study is to estimate the mandibular growth stage based on cervical vertebral maturation (CVM) in lateral cephalometric radiographs using artificial intelligence. Unlike previous studies, which use conventional CVM stage naming, our pr...

High-performing cross-dataset machine learning reveals robust microbiota alteration in secondary apical periodontitis.

Multiple research groups have consistently underscored the intricate interplay between the microbiome and apical periodontitis. However, the presence ...

A supramolecular fluorescence sensor array for the differentiation of multiple anions and prediction of iodine in artificial urine using machine learning.

The simultaneous discrimination and detection of multiple anions in an aqueous solution has been a major challenge due to their structural similarity ...

Interpreting optimised data-driven solution with explainable artificial intelligence (XAI) for water quality assessment for better decision-making in pollution management.

In Saudi Arabia, water pollution and drinking water scarcity pose a major challenge and jeopardise the achievement of sustainable development goals. T...

Exploring the Impact of the Class on In-the-Wild Human Activity Recognition.

Monitoring activities of daily living (ADLs) plays an important role in measuring and responding to a person's ability to manage their basic physical ...

Prediction of Interactomic HUB Genes in Periodontitis With Acute Myocardial Infarction.

BACKGROUND: Acute myocardial infarction (AMI) risk correlates with C-reactive protein (CRP) levels, suggesting systemic inflammation is present well b...

Evaluation of different machine learning algorithms for extraction decision in orthodontic treatment.

INTRODUCTION: The extraction decision significantly affects the treatment process and outcome. Therefore, it is crucial to make this decision with a m...

A reliable deep-learning-based method for alveolar bone quantification using a murine model of periodontitis and micro-computed tomography imaging.

OBJECTIVES: This study focuses on artificial intelligence (AI)-assisted analysis of alveolar bone for periodontitis in a mouse model with the aim to c...

Automatic cephalometric landmark identification with artificial intelligence: An umbrella review of systematic reviews.

OBJECTIVES: The transition from manual to automatic cephalometric landmark identification has not yet reached a consensus for clinical application in ...

Transferability of Machine Learning Models for Geogenic Contaminated Groundwaters.

Machine learning models show promise in identifying geogenic contaminated groundwaters. Modeling in regions with no or limited samples is challenging ...

Artificial intelligence as a prediction tool for orthognathic surgery assessment.

INTRODUCTION: An ideal orthodontic treatment involves qualitative and quantitative measurements of dental and skeletal components to evaluate patients...

Role of artificial intelligence in behavior management of pediatric dental patients-a mini review.

The influence of behavioral science on various organizations has been experiencing remarkable growth worldwide. With the integration of recent technol...

Artificial Intelligence in Orthodontics: Critical Review.

With increasing digitalization in orthodontics, certain orthodontic manufacturing processes such as the fabrication of indirect bonding trays, aligner...

Detecting white spot lesions on post-orthodontic oral photographs using deep learning based on the YOLOv5x algorithm: a pilot study.

BACKGROUND: Deep learning model trained on a large image dataset, can be used to detect and discriminate targets with similar but not identical appear...

Enhanced control of periodontitis by an artificial intelligence-enabled multimodal-sensing toothbrush and targeted mHealth micromessages: A randomized trial.

AIM: Treatment of periodontitis, a chronic inflammatory disease driven by biofilm dysbiosis, remains challenging due to patients' poor performance and...

Accuracy of Artificial Intelligence Models in the Prediction of Periodontitis: A Systematic Review.

INTRODUCTION: Periodontitis is the main cause of tooth loss and is related to many systemic diseases. Artificial intelligence (AI) in periodontics has...

Artificial Q-Grader: Machine Learning-Enabled Intelligent Olfactory and Gustatory Sensing System.

Portable and personalized artificial intelligence (AI)-driven sensors mimicking human olfactory and gustatory systems have immense potential for the l...

Amino-functionalized novel biosorbent for effective removal of fluoride from water: process optimization using artificial neural network and mechanistic insights.

Aqueous fluoride ( ) pollution is a global threat to potable water security. The present research envisions the development of novel adsorbents from ...

The performance of artificial intelligence models in generating responses to general orthodontic questions: ChatGPT vs Google Bard.

INTRODUCTION: This study aimed to evaluate and compare the performance of 2 artificial intelligence (AI) models, Chat Generative Pretrained Transforme...