JDR clinical and translational research
Apr 25, 2018
Researchers have suggested that combining topical fluoride with an antiseptic to reduce cariogenic bacteria may be more effective than fluoride application alone in preventing dental caries. In previous studies, povidone iodine (PVP-I), a widely used...
OBJECTIVE: This study aimed to demonstrate the use of deep learning for automating caries detection using intraoral scan data from children and to evaluate diagnostic agreement between the models' predictions and dental practitioner assessments on 3D...
Dental caries is one of the most prevalent chronic diseases among both children and adults, despite being largely preventable. This condition has significant negative impacts on human health and imposes a substantial economic burden. In recent years,...
Despite a decrease in the incidence of dental caries over the past four decades, it remains a widespread public health concern. The multifactorial etiology of dental caries complicates effective prevention and early intervention efforts, underscoring...
STATEMENT OF PROBLEM: Automated detection of dental caries could enhance early detection, save clinician time, and enrich treatment decisions. However, a reliable system is lacking.
To assess the diagnostic and treatment decision-making accuracy of ChatGPT for various dental problems in pediatric patients compared to specialized pediatric dentists. This study included 12 cases, each with an average of three dental problems, re...
Quintessence international (Berlin, Germany : 1985)
Jan 30, 2025
Dental caries is one of the most common diseases globally. It affects children and adults living in poverty, who have the most limited access to dental care. Left unexamined and untreated in the early stages, treatments for late-stage and severe cari...
UNLABELLED: Artificial Intelligence (AI) has emerged as one of the most significant innovations in dentistry, enabling the efficient analysis of large volumes of data and enhancing the quality of diagnosis and treatment.
To conduct a systematic review of artificial intelligence (AI) in aiding clinicians with the prediction and detection specifically for early childhood caries (ECC). A search was performed across PubMed, Scopus, Web of Science, IEEE, and grey litera...
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...
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