85 results match your criteria: "Wonkwang University College of Dentistry[Affiliation]"

Performance of Large Language Models on the Korean Dental Licensing Examination: A Comparative Study.

Int Dent J

October 2024

Department of Oral and Maxillofacial Radiology, Daejeon Dental Hospital, Wonkwang University College of Dentistry, Daejeon, Korea. Electronic address:

Purpose: This study investigated the potential application of large language models (LLMs) in dental education and practice, with a focus on ChatGPT and Claude3-Opus. Using the Korean Dental Licensing Examination (KDLE) as a benchmark, we aimed to assess the capabilities of these models in the dental field.

Methods: This study evaluated three LLMs: GPT-3.

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Deep learning-based prediction of indication for cracked tooth extraction using panoramic radiography.

BMC Oral Health

August 2024

Department of Biomedical Engineering, College of IT Convergence, Gachon University, Gyeonggi-do, Republic of Korea.

Background: We aimed to determine the feasibility of utilizing deep learning-based predictions of the indications for cracked tooth extraction using panoramic radiography.

Methods: Panoramic radiographs of 418 teeth (group 1: 209 normal teeth; group 2: 209 cracked teeth) were evaluated for the training and testing of a deep learning model. We evaluated the performance of the cracked diagnosis model for individual teeth using InceptionV3, ResNet50, and EfficientNetB0.

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Background: Positron emission tomography (PET) has been reported as effective in diagnosing peripheral nerve injury (PNI). However, there is a lack of studies evaluating different degrees of PNI using PET within the same individual to reduce errors due to interindividual differences.

Purpose: To evaluate the recovery process in the same rat after sciatic nerve injury using PET/magnetic resonance imaging (MRI).

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Background: Since most of the commonly known oral diseases are explained in link with balance of microbial community, an accurate bacterial taxonomy profiling for determining bacterial compositional network is essential. However, compared to intestinal microbiome, research data pool related to oral microbiome is small, and general 16S rRNA screening method has a taxonomy misclassification issue in confirming complex bacterial composition at the species level.

Objective: Present study aimed to explore bacterial compositional networks at the species level within saliva of 39 oral disease patients (Dental Caries group: n = 26 and Periodontitis group: n = 13) through comparison with public Korean-specific healthy oral microbiome data.

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Purpose: Bone quality is one of the most important clinical factors for the primary stability and successful osseointegration of dental implants. This preliminary pilot study aimed to evaluate the clinical applicability of deep learning (DL) for assessing bone quality using panoramic (PA) radiographs compared with an implant surgeon's subjective tactile sense and cone-beam computed tomography (CBCT) values.

Methods: In total, PA images of 2,270 edentulous sites for implant placement were selected, and the corresponding CBCT relative gray value measurements and bone quality classification were performed using 3-dimensional dental image analysis software.

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Although the lateral window approach allows for greater graft material delivery and bone formation, it is more challenging and invasive, prompting keen interest among dentists to master this method. YouTube is increasingly used for medical training; however, concerns regarding the quality of instructional videos exist. This study proposes new criteria for evaluating YouTube videos on maxillary sinus elevation with the aim of establishing standards for assessing instructional content in the field.

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Background: This study explored dental students' and dentists' perceptions and attitudes toward artificial intelligence (AI) and analyzed differences according to professional seniority.

Methods: In September to November 2022, online surveys using Google Forms were conducted at 2 dental colleges and on 2 dental websites. The questionnaire consisted of general information (8 or 10 items) and participants' perceptions, confidence, predictions, and perceived future prospects regarding AI (17 items).

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The effect of Schizophyllan on the differentiation of osteoclasts and osteoblasts.

Biochem Biophys Res Commun

May 2024

Department of Molecular Genetics, School of Dentistry and Dental Research Institute, Seoul National University, Seoul, 08826, Republic of Korea. Electronic address:

Schizophyllan (SPG), a β-glucan from Schizophyllum commune, is recognized for its antioxidant, immunoregulatory, and anticancer activities. In this study, its effects on bone cells, particularly osteoclasts and osteoblasts, were examined. We demonstrated that SPG dose-dependently inhibited osteoclastogenesis and reduced gene expression associated with osteoclast differentiation.

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Objective: To evaluate the profilometric, esthetic, and patient-reported outcomes of peri-implant tissues in the maxillary anterior esthetic zone following guided bone regeneration (GBR) using the L-shape technique combined with delayed connective tissue grafting (CTG).

Materials And Methods: Profilometric and pink esthetic score (PES) measurements were performed at the time of implant surgery with GBR (T0) and at the 1- (T1), 2- (T2), and 3-year (T3) follow-up. Patient-reported outcomes were also assessed using the Oral Health Impact Profile-14 (OHIP-14) questionnaire.

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Long-term results of regenerative treatment of intrabony defects: a cohort study with 5-year follow-up.

BMC Oral Health

January 2024

Department of Periodontology, Daejeon Dental Hospital, Institute of Wonkwang Dental Research, Wonkwang University College of Dentistry, Daejeon, Korea.

Background: The aim of this retrospective cohort study was to evaluate the long-term clinical and radiographic outcomes and survival of teeth in periodontal regenerative treatment of intrabony defects using combined enamel matrix protein derivative (EMD) and deproteinized porcine bone mineral (DPBM) compared to EMD alone.

Methods: A total of 333 intrabony defects in 176 patients (mean age: 54.7 ± 8.

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Purpose: Alveolar ridge preservation (ARP) was introduced to minimize postextraction alveolar bone loss and extraction socket remodeling; however, current knowledge of the ARP procedure for nonintact extraction sockets is still limited and inconclusive. This retrospective study aimed to evaluate the difference between using deproteinized bovine bone mineral with 10% collagen (DBBM-C) and deproteinized porcine bone mineral with 10% collagen (DPBM-C) when performing ARP procedures in damaged or periodontally compromised extraction sockets based on clinical, radiographic, and profilometric outcomes.

Methods: In total, 108 extraction sockets were grafted with 67 DBBM-C and 41 DPBM-C.

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Purpose: No evidence exists regarding the advantages of periodontal regeneration treatment for furcation defects using soft block bone substitutes. Therefore, this randomized controlled trial aimed to assess the clinical and radiographic outcomes of regenerative therapy using porcine-derived soft block bone substitutes (DPBM-C, test group) compared with porcine-derived particulate bone substitutes (DPBM, control group) for the treatment of severe class II furcation defects in the mandibular molar regions.

Methods: Thirty-five enrolled patients (test group, n=17; control group, n=18) were available for a 12-month follow-up assessment.

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Background: In this study, we investigated whether deep learning-based prediction of osseointegration of dental implants using plain radiography is possible.

Methods: Panoramic and periapical radiographs of 580 patients (1,206 dental implants) were used to train and test a deep learning model. Group 1 (338 patients, 591 dental implants) included implants that were radiographed immediately after implant placement, that is, when osseointegration had not yet occurred.

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Oral microbial ecosystem could influence intestinal diseases, but there have been insufficient studies demonstrating the association of microbial composition between the oral cavity and the intestinal system. Thus, we aimed to investigate the compositional network within the oral microbiome related to gut enterotype from saliva and stool samples collected from 112 healthy Korean subjects. Here, we performed bacterial 16S amplicon sequencing from clinical samples.

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Purpose: The aim of this study was to investigate the risk of periodontitis according to current smoking status based on the number of cigarettes smoked per day (CPD) and the Fagerström Test for Nicotine Dependence (FTND).

Methods: All enrolled patients were diagnosed and classified according to the new periodontal classification scheme, and current smoking status was investigated via a self-reported questionnaire. The correlation between smoking status (CPD and FTND) and periodontitis risk (severity of periodontitis and tooth loss due to periodontal reasons) was statistically assessed using Spearman correlation coefficients.

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Purpose: In this study, we aimed to evaluate the degree of heat generation when a novel drill design with an irrigation slot was used with metal sleeve-free (MF) and metal sleeve-incorporated (MI) surgical guides in an environment similar to that of the actual oral cavity.

Methods: A typodont with a missing mandibular right first molar and 21 bovine rib blocks were used. Three-dimensional-printed MF and MI surgical guides, designed for the placement of internal tapered implant fixtures, were used with slot and non-slot drills.

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Purpose: The purpose of this study was to compare the microbial composition of 3 types of oral samples through 16S metagenomic sequencing to determine how to resolve some sampling issues that occur during the collection of sub-gingival plaque samples.

Methods: In total, 20 subjects were recruited. In both the healthy and periodontitis groups, samples of saliva and supra-gingival plaque were collected.

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Special Issue "Artificial Intelligence in Oral Health".

Diagnostics (Basel)

August 2022

Department of Periodontology, Daejeon Dental Hospital, Institute of Wonkwang Dental Research, Wonkwang University College of Dentistry, Daejeon 35233, Korea.

I thank all authors, reviewers and the editorial staff who contributed to this Special Issue [...

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Deep learning in periodontology and oral implantology: A scoping review.

J Periodontal Res

October 2022

Topic Group Dental Diagnostics and Digital Dentistry, ITU/WHO Focus Group AI on Health, Berlin, Germany.

Deep learning (DL) has been employed for a wide range of tasks in dentistry. We aimed to systematically review studies employing DL for periodontal and implantological purposes. A systematic electronic search was conducted on four databases (Medline via PubMed, Google Scholar, Scopus, and Embase) and a repository (ArXiv) for publications after 2010, without any limitation on language.

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Deep learning improves implant classification by dental professionals: a multi-center evaluation of accuracy and efficiency.

J Periodontal Implant Sci

June 2022

Department of Periodontology, Daejeon Dental Hospital, Institute of Wonkwang Dental Research, Wonkwang University College of Dentistry, Daejeon, Korea.

Purpose: The aim of this study was to evaluate and compare the accuracy performance of dental professionals in the classification of different types of dental implant systems (DISs) using panoramic radiographic images with and without the assistance of a deep learning (DL) algorithm.

Methods: Using a self-reported questionnaire, the classification accuracy of dental professionals (including 5 board-certified periodontists, 8 periodontology residents, and 31 dentists not specialized in implantology working at 3 dental hospitals) with and without the assistance of an automated DL algorithm were determined and compared. The accuracy, sensitivity, specificity, confusion matrix, receiver operating characteristic (ROC) curves, and area under the ROC curves were calculated to evaluate the classification performance of the DL algorithm and dental professionals.

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Purpose: The aim of this study was to evaluate 1-year stability and maintenance of peri-implant soft and hard tissues after guided bone regeneration (GBR) with L-shaped collagenated bone substitute and subepithelial connective tissue graft (CTG) in the maxillary anterior region using profilometric, volumetric, and esthetic analyses.

Methods: Fourteen peri-implant defects were grafted with L-shaped collagenated bone substitute, and 5 months after implant placement with GBR, reentry surgery in combination with CTG was performed in all participants. CBCT scans and STL files were acquired at baseline (after implant surgery, T1), reentry surgery (T2), and 1-year follow-up (T3).

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In this study, we evaluated changes in the masseter and lateral pterygoid muscles in the prognathic mandible group after a mandibular setback by comparing the volume-to-length ratios. Preoperative and postoperative 1-year computed tomography was used to calculate the volume-to-length ratio of the lateral pterygoid and masseter muscle in 60 Korean individuals. Three-dimensional images were reconstructed, the results of which showed no significant differences in the volume-to-length ratios of the masseter and lateral pterygoid muscles after a mandibular setback (p > 0.

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Augmentation Stability of Guided Bone Regeneration for Peri-Implant Dehiscence Defects with L-shaped Porcine-Derived Block Bone Substitute.

Materials (Basel)

November 2021

Department of Periodontology, Daejeon Dental Hospital, Institute of Wonkwang Dental Research, Wonkwang University College of Dentistry, Daejeon 35233, Korea.

Block bone substitutes have better augmentation stability for guided bone regeneration (GBR) than particulate bone substitutes. This study sought to determine whether GBR with an L-shaped porcine block bone (DPBM-C) differs from GBR with an L-shaped bovine block bone (DBBM-C) based on clinical, radiographic, and volumetric outcomes for peri-implant dehiscence defects. A total of 42 peri-implant defects were grafted with 20 L-shaped DPBM-C and 22 DBBM-C groups.

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Article Synopsis
  • * Researchers analyzed a dataset of 300 preoperative images, with 100 from patients who experienced paresthesia post-surgery and 200 from those who didn't, dividing them into training, validation, and test sets.
  • * The results showed that the CNN models achieved a good performance, with an average accuracy of 82.7%, suggesting that these models can be useful tools for predicting nerve issues in dental procedures.
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Background: The aim of this study was to report a rare case of nasopalatine duct cyst with sebaceous differentiation. Further, a systematic search of the literature was performed to identify studies reporting patients with intraosseous jaw cysts with sebaceous differentiation.

Case Presentation: A 55-year-old Korean man was referred to our hospital because of a cystic lesion of the anterior maxilla.

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