Dental Health

Geochemical evolution, geostatistical mapping and machine learning predictive modeling of groundwater fluoride: a case study of western Balochistan, Quetta.

Around 2.6 billion people are at risk of tooth carries and fluorosis worldwide. Quetta is the worst affected district in Balochistan plateau. Endemic abnormal groundwater fluoride ( ) lacks spatiotemporal studies. This research integrates geospatial distribution, geochemical signatures, and data driven method for evaluating levels and population at risk. Groundwater ranged from 0 to 3.4 mg/l in...

Analysis of the basement membrane-related genes ITGA7 and its regulatory role in periodontitis via machine learning: a retrospective study.

BACKGROUND: Periodontitis is among the most prevalent inflammatory conditions and greatly impacts oral health. This study aimed to elucidate the role of basement membrane-related genes in the pathogenesis and diagnosis of periodontitis.

Recent advances in groundwater pollution research using machine learning from 2000 to 2023: A bibliometric analysis.

Groundwater pollution has become a global challenge, posing significant threats to human health and ecological environments. Machine learning, with it...

Biofilm architecture and dynamics of the oral ecosystem.

The oral cavity, being a nutritionally enriched environment, has been proven to be an ideal habitat for biofilm development. Various microenvironments...

Antimicrobial activity of L. Pers against periodontal pathogen: .

BACKGROUND: is widely recognised as a periodontal pathogen. In recent years, there has been growing interest in the use of medicinal plant extracts a...

Machine Learning and Mendelian Randomization Reveal Molecular Mechanisms and Causal Relationships of Immune-Related Biomarkers in Periodontitis.

This study aimed to investigate the molecular mechanisms of periodontitis and identify key immune-related biomarkers using machine learning and Mendel...

Exploring the risk factors and clustering patterns of periodontitis in patients with different subtypes of diabetes through machine learning and cluster analysis.

AIM: To analyse the risk factors contributing to the prevalence of periodontitis among clusters of patients with diabetes and to examine the clusterin...

Oral Microbe Community and Pyramid Scene Parsing Network-based Periodontitis Risk Prediction.

BACKGROUND: Periodontitis (PD) is a common chronic inflammatory disease affecting the gums and supporting tooth structures. It is often diagnosed only...

Development of an Artificial Intelligence-Based Algorithm for the Assessment of Skeletal Age and Detection of Cervical Vertebral Anomalies in Patients with Cleft Lip and Palate.

ObjectiveTo develop an artificial intelligence (AI)-based algorithm for the assessment and comparison of skeletal maturation in patients with and with...

Genetic analysis of potential markers and therapeutic targets for immunity in periodontitis.

OBJECTIVE: Periodontitis is a chronic inflammatory periodontal disease resulting in destroyed periodontal tissue. Many studies have found that the hos...

A personalized periodontitis risk based on nonimage electronic dental records by machine learning.

OBJECTIVE: This study aimed to develop a machine-learning (ML) model to predict the risk for Periodontal Disease (PD) based on nonimage electronic den...

A Fully Integrated Orthodontic Aligner With Force Sensing Ability for Machine Learning-Assisted Diagnosis.

Currently, the diagnosis of malocclusion is a highly demanding process involving complicated examinations of the dental occlusion, which increases the...

Explainable Deep Learning Approaches for Risk Screening of Periodontitis.

Several pieces of evidence have been reported regarding the association between periodontitis and systemic diseases. Despite the emphasized significan...

Unravelling integrated groundwater management in pollution-prone agricultural cities: A synergistic approach combining probabilistic risk, source apportionment and artificial intelligence.

Groundwater is vital for agricultural cities, but intensive farming and fertilizer use have increased contamination risks, particularly for non-carcin...

Training, use, and modifications related to artificial intelligence in postgraduate orthodontic programs in North America.

INTRODUCTION: The use of artificial intelligence (AI) is growing quickly and has already had a significant impact on the practice of orthodontics. Thi...

Automatic 3-dimensional quantification of orthodontically induced root resorption in cone-beam computed tomography images based on deep learning.

INTRODUCTION: Orthodontically induced root resorption (OIRR) is a common and undesirable consequence of orthodontic treatment. Traditionally, studies ...

Artificial intelligence for orthodontic diagnosis and treatment planning: A scoping review.

OBJECTIVES: To provide an overview of artificial intelligence (AI) applications in orthodontic diagnosis and treatment planning, and to evaluate wheth...

Segmentation of periapical lesions with automatic deep learning on panoramic radiographs: an artificial intelligence study.

Periapical periodontitis may manifest as a radiographic lesion radiographically. Periapical lesions are amongst the most common dental pathologies tha...

Enhancing local-scale groundwater quality predictions using advanced machine learning approaches.

Assessing groundwater quality typically involves labor-intensive, time-consuming, and costly laboratory tests, making real-time monitoring impractical...

Comparison of semi and fully automated artificial intelligence driven softwares and manual system for cephalometric analysis.

BACKGROUND: Cephalometric analysis has been used as one of the main tools for orthodontic diagnosis and treatment planning. The analysis can be perfor...