Perceptions and attitudes of dental students and dentists in South Korea toward artificial intelligence: a subgroup analysis based on professional seniority.

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). A multivariate logistic regression analysis was performed on 4 questions representing perceptions and attitudes toward AI to identify highly influential factors according to position, age, sex, residence, and self-reported knowledge level about AI of respondents. Participants were reclassified into 2 subgroups based on students' years in school and 4 subgroups based on dentists' years of experience. The chi-square test or Fisher's exact test was used to determine differences between dental students and dentists and between subgroups for all 17 questions. RESULTS: The study included 120 dental students and 96 dentists. Participants with high level of AI knowledge were more likely to be interested in AI compared to those with moderate or low level (adjusted OR 24.345, p < 0.001). Most dental students (60.8%) and dentists (67.7%) predicted that dental AI would complement human limitations. Dental students responded that they would actively use AI in almost all cases (40.8%), while dentists responded that they would use AI only when necessary (44.8%). Dentists with 11-20 years of experience were the most likely to disagree that AI could outperform skilled dentists (50.0%), and respondents with longer careers had higher response rates regarding the need for AI education in schools. CONCLUSIONS: Knowledge level about AI emerged as the factor influencing perceptions and attitudes toward AI, with both dental students and dentists showing similar views on recognizing the potential of AI as an auxiliary tool. However, students' and dentists' willingness to use AI differed. Although dentists differed in their confidence in the abilities of AI, all dentists recognized the need for education on AI. AI adoption is becoming a reality in dentistry, which requires proper awareness, proper use, and comprehensive AI education.

Evaluation of residual dentin thickness using quantitative light-induced fluorescence technology.

This study aimed to determine whether a correlation exists between residual dentin thickness and quantitative light-induced fluorescence (QLF) values and, if so, to analyze its tendencies. Forty extracted sound human molars were assigned to filled and unfilled groups. The teeth were submerged in a mold with clear acrylic resin. Red utility wax was inserted into the pulp chamber space in the filled group to simulate vital pulp. The specimen was sectioned longitudinally to observe the inside of the pulp space. The samples were cut horizontally from the highest point of the pulp space 2 mm apart. QLF images were then taken of 2 mm, 1 mm, and 0.5 mm samples using the QLF-D Biluminator™ 2 + system. Three operators independently evaluated the QLF images, and the statistical analysis was conducted using one-way analysis of variance, Pearson correlation coefficients, and intraclass correlation coefficients. In the filled group, the mean ΔF values for residual dentin thicknesses of 2 mm, 1 mm, and 0.5 mm were - 3.22, - 7.84, and - 11.52, respectively. In the unfilled group, the mean ΔF values were 0, - 6.90, and - 10.14, respectively. A positive correlation was found between residual dentin thickness and ΔF values (P < 0.05). The intraclass correlation coefficients for observations made by the three operators for the filled and unfilled groups were 0.831 and 0.917, respectively (P < 0.05). In conclusion, residual dentin thickness and ΔF values were significantly correlated and had a highly positive correlation regardless of the QLF device operator.

Simple oral exercise with chewing gum for improving oral function in older adults.

BACKGROUND: As general and oral health are closely interrelated, promoting oral health may extend a healthy life expectancy. AIMS: To evaluate the long-term effects of simple oral exercise (SOE) and chewing gum exercise on mastication, salivation, and swallowing function in adults aged ≥ 65 years. METHODS: Ninety-six participants were assigned to control, SOE, and GOE (chewing gum exercise with SOE) groups. The SOE comprised exercises to improve mastication, salivation, and swallowing function. Control group participants performed no exercises. The intervention period was 8 weeks, followed by a 3-week maintenance period. The Mixing Ability Index (MAI), occlusal force, unstimulated saliva, and repetitive saliva swallowing test were evaluated at baseline and 2, 5, 8, and 11 weeks later. Self-reported discomfort was re-evaluated after 8 weeks. RESULTS: After 8 weeks, mean MAI differences from baseline significantly increased in both groups; the increase in the GOE group was largest and four times higher than in the control group. Mean differences of occlusal force from baseline increased by 56 N (SOE group) and 60 N (GOE group). The increase of salivation was greater in the SOE (3.6-fold) and GOE (2.2-fold) groups than in the control group. Furthermore, 27% and 18% of SOE and GOE group participants, respectively, were re-categorized as having good swallowing function. Participants reported less discomfort as oral functions improved. DISCUSSION: These findings may facilitate the development of clinical practice guidelines for optimal oral care in older adults. CONCLUSION: While both SOE and GOE may improve oral function in older adults, GOE is recommended for those with impaired mastication. TRIAL REGISTRATION: KCT0003305, retrospectively registered 31/10/2018.

Dentists' clinical decision-making about teeth with apical periodontitis using a variable-controlled survey model in South Korea.

BACKGROUND: This study, by using a variable-controlled survey model, sought to compare clinical decisions made by dentists with different clinical backgrounds in South Korea regarding teeth with apical periodontitis and to identify factors that influenced decision-making. METHODS: A questionnaire with 36 questions about identical patient information, clinical signs, and symptoms was filled out by participants. Each question referred to a radiograph that had been manipulated using computer software in order to control tooth-related factors. Participants were instructed to record their demographic information and choose the ideal treatment option related to each radiograph. Simple and multivariable logistic regression analyses (p < .05) were used to investigate factors related to the decision to extract the tooth. We divided factors into dentist-related factors (gender, years of experience, and professional registration) and tooth-related factors (tooth position, coronal status, root canal filling status, and size of the periapical radiolucency). Dentists were categorized into three groups, based on professional registration: general dental practitioners (GDPs), endodontists, and other specialists. Simple logistic regression analysis (p < .05) was used to evaluate the tooth-related factors influencing extraction, depending on the dentists' specialty. RESULTS: Participants mostly preferred saving the teeth over extraction. This preference was highest among the endodontists, followed by other specialists and GDPs. Extractions were significantly preferred for molars, teeth with previous root canal fillings, and those with apical lesions greater than 5 mm. CONCLUSIONS: This study suggests that dentists' decision-making regarding teeth with apical periodontitis was associated with their work experience and specialty and influenced by tooth position, root canal filling status, and size of the apical lesion. CLINICAL RELEVANCE: This survey revealed that clinical decision-making related to teeth with apical periodontitis was affected by dentists' specialty and work experience and by tooth-related factors, such as tooth position, root canal filling status, and size of the apical lesion.

Unilateral Mastication Evaluated Using Asymmetric Functional Tooth Units as a Risk Indicator for Hearing Loss.

BACKGROUND: Some previous studies reported hearing ability can be reduced by impaired masticatory ability, but there has been little evidence reported of an association between hearing loss and unilateral mastication. Therefore, this study aimed to investigate the relationship between unilateral mastication (UM), estimated from individual functional tooth units (FTUs), and hearing loss in a representative sample of Korean adults. METHODS: The analyzed data were obtained from 1,773 adults aged 40-89 years who participated in Korean national survey. Hearing loss was defined as a pure-tone average of >25 dB at frequencies of 0.5, 1, 2, and 4 kHz in either ear. In each subject, UM was calculated as the difference in the sums of the FTU scores, which is an index of posterior tooth occlusion, on the two sides of the oral cavity. The scores were used to classify the UM into low, moderate, and high. The adjusted odds ratios (aORs) and their 95% confidence intervals (CIs) were calculated in multivariable logistic regression analyses. RESULTS: When controlling for sociodemographic factors, the aOR for hearing loss was 3.12 (95% CI, 1.21-8.03) for high UM relative to low UM. This association remained in a fully-adjusted model containing factors related to noise exposure (aOR 2.88; 95% CI, 1.12-7.46). CONCLUSION: Adults with high UM as measured using FTUs showed a higher occurrence of hearing loss than those with low UM.

Does the national dental scaling policy reduce inequalities in dental scaling usage? A population-based quasi-experimental study.

BACKGROUND: In 2013, the national dental scaling insurance policy was introduced in South Korea. The purpose of this study is to determine the impact of the policy on inequalities in dental scaling usage. METHODS: Data of a nationally representative sample of 1,517,097 people over the age of 20 were obtained from the 2010-2016 Community Health Survey. Respondents who reported that they had not received dental scaling in the past year were defined as dental scaling non-users. The excess prevalence and relative prevalence ratio of dental scaling non-users were calculated for the pre-policy (2010-2012) and post-policy periods (2014-2016) using monthly household income levels. Additionally, trends of dental scaling inequalities were shown as concentration indexes. RESULTS: The prevalence of dental scaling non-users declined from 58.0 to 48.7% in the highest income group and from 86.3 to 78.8% in the lowest income group. However, the adjusted excess prevalence for the lowest income group compared with the highest had increased from 11.9 (95% CI: 11.9-11.9) to 15.5 (95% CI: 15.5-15.5)%, and the adjusted prevalence ratio increased from 1.19 (95% CI: 1.19-1.20) to 1.29 (95% CI: 1.29-1.30). Absolute and relative concentration indexes of dental scaling non-users increased after policy implementation. CONCLUSIONS: The national dental scaling insurance policy has increased socioeconomic inequalities in dental scaling usage. Because dental care access generally requires high individual agency, expanded dental coverage may have had limited effects in attenuating inequalities and inadvertently widened the gap. To reduce dental care inequalities, universal access with universal dental coverage should be considered.

Comparison of the effect of endodontic-periodontal combined lesion on the outcome of endodontic microsurgery with that of isolated endodontic lesion: survival analysis using propensity score analysis.

OBJECTIVES: The purpose of this retrospective clinical study was to evaluate the effect of lesion types related to endodontic microsurgery on the clinical outcome. MATERIALS AND METHODS: Patients who underwent endodontic microsurgery between March 2001 and March 2014 with a postoperative follow-up period of at least 1 year were included in the study. Survival analyses were conducted to compare the clinical outcomes between isolated endodontic lesion group (endo group) and endodontic-periodontal combined lesion group (endo-perio group) and to evaluate other clinical variables. To reduce the effect of selection bias in this study, the estimated propensity scores were used to match the cases of the endo group with those of the endo-perio group. RESULTS: Among the 414 eligible cases, the 83 cases in the endo-perio group were matched to 166 out of the 331 cases in the endo group based on propensity score matching (PSM). The cumulated success rates of the endo and endo-perio groups were 87.3 and 72.3%, respectively. The median success period of the endo-perio group was 12 years (95% CI: 5.507, 18.498). Lesion type was found to be significant according to both Log-rank test (P = 0.002) and Cox proportional hazard regression analysis (P = 0.001). Among the other clinical variables, sex (female or male), age, and tooth type (anterior, premolar, or molar) were determined to be significant in Cox regression analysis (P < 0.05). CONCLUSION: Endodontic-periodontal combined lesions had a negative effect on the clinical outcome based on an analysis that utilized PSM, a useful statistical matching method for observational studies. CLINICAL RELEVANCE: Lesion type is a significant predictor of the outcome of endodontic microsurgery.

Alveolar Molding Effect in Infants With Unilateral Cleft Lip and Palate: Comparison of Two- and Three-Dimensional Measurements.

The purpose of this study was to compare the results of two- (2D) and three-dimensional (3D) measurements for the alveolar molding effect in patients with unilateral cleft lip and palate. The sample consisted of 23 unilateral cleft lip and palate infants treated with nasoalveolar molding (NAM) appliance. Dental models were fabricated at initial visit (T0; mean age, 23.5 days after birth) and after alveolar molding therapy (T1; mean duration, 83 days). For 3D measurement, virtual models were constructed using a laser scanner and 3D software. For 2D measurement, 1:1 ratio photograph images of dental models were scanned by a scanner. After setting of common reference points and lines for 2D and 3D measurements, 7 linear and 5 angular variables were measured at the T0 and T1 stages, respectively. Wilcoxon signed rank test and Bland-Altman analysis were performed for statistical analysis. The alveolar molding effect of the maxilla following NAM treatment was inward bending of the anterior part of greater segment, forward growth of the lesser segment, and decrease in the cleft gap in the greater segment and lesser segment. Two angular variables showed difference in statistical interpretation of the change by NAM treatment between 2D and 3D measurements (ΔACG-BG-PG and ΔACL-BL-PL). However, Bland-Altman analysis did not exhibit significant difference in the amounts of change in these variables between the 2 measurements. These results suggest that the data from 2D measurement could be reliably used in conjunction with that from 3D measurement.

Distinguishing discolored caries lesions using biofluorescence and dental bleaching: An in vitro simulation model study.

BACKGROUND: Distinguishing between discoloration caused by caries and organic stains is challenging for dentists in clinical settings. Biofluorescence (BF)-bleaching assesses caries lesions by evaluating BF changes after removing organic stains through dental bleaching, leaving cariogenic discoloration. This study aimed to apply BF-bleaching to a simulation model mimicking cariogenic discoloration and compare the BF color changes between organic staining and cariogenic discoloration. METHODS: Thirty artificial caries lesions in bovine incisors were equally divided into three groups: non-stained (NS), organic-stained (OS), and cariogenic-stained (CS) groups. The specimens were treated with bleaching agent, then BF color of each specimen was evaluated using red BF intensity (ΔR), BF hue angle (h°), and hyperspectral BF spectrum. RESULTS: The ΔR of CS was approximately 2.74 and 1.73 times higher than that of OS, at baseline and after bleaching for 20 min, respectively. After 20 min of bleaching, the h° of CS increased by approximately 8.1° compared to the baseline, while maintaining the red BF hue range (345‒15°). In contrast, the BF hue of OS shifted from orange (15‒45°) to yellow (45‒75°) simultaneously, and the h° change was approximately 21.9°. Both CS and OS exhibited first emission peaks near 515 nm, and CS showed second peaks in the red range (620‒780 nm). After bleaching, the first peaks were restored to the sound enamel direction (peak at 486 nm), whereas the second peaks of red BF in CS were maintained. CONCLUSION: Applying BF-bleaching to discolored caries lesions allowed differentiation between cariogenic discoloration and organic staining based on BF color changes.

Evaluation metric of smile classification by peri-oral tissue segmentation for the automation of digital smile design.

OBJECTIVES: This study aimed to develop and validate evaluation metric for an automated smile classification model termed the "smile index." This innovative model uses computational methods to numerically classify and analyze conventional smile types. METHODS: The datasets used in this study consisted of 300 images to verify, 150 images to validate, and 9 images to test the evaluation metric. Images were annotated using Labelme. Computational techniques were used to calculate smile index values for the study datasets, and the resulting values were evaluated in three stages. RESULTS: The smile index successfully classified smile types using cutoff values of 0.0285 and 0.193. High accuracy (0.933) was achieved, along with an F1 score greater than 0.09. The smile index successfully reclassified smiles into six types (low, low-to-medium, medium, medium-to-high, high, and extremely high smiles), thereby providing a clear distinction among different smile characteristics. CONCLUSION: The smile index is a novel dimensionless parameter for classifying smile types. The index acts as a robust evaluation tool for artificial intelligence models that automatically classify smile types, thereby providing a scientific basis for largely subjective aesthetic elements. CLINICAL SIGNIFICANCE: The computational approach employed by the smile index enables quantitative numerical classification of smile types. This fosters the application of computerized methods in quantifying and analyzing real smile characteristics observed in clinical practice, paving the way for a more objective evidence-based approach to aesthetic dentistry.

Trend in the Incidence of Severe Partial Edentulism among Adults Using the Korean National Health Insurance Service Claim Data, 2014-2018.

PURPOSE: Missing teeth is one of the most important indicators of oral health behavior and the result of dental caries, periodontal disease, and injuries. This study examined a trend in the incidence of severe partial edentulism (SPE) using the Korean National Health Insurance Service (KNHIS) data. MATERIALS AND METHODS: Data of adults aged ≥20 years were obtained from the KNHIS for the 2014-2018 period. SPE was defined in dental information within a population with a treatment history of dental scaling as having 1 to 8 natural teeth. Crude incidence rates (CIRs) and age-standardized incidence rates (AIRs) with 95% confidence interval were calculated per 100000 persons. The Cochran Armitage trend (CAT) test and average annual percentage change were used to analyze SPE trends. RESULTS: The CIRs among Korean adults were from 346.29 to 391.11 in 2014-2016 and from 391.11 to 354.09 in 2016-2018. The AIRs trend statistically increased by 4.31% from 346.29 to 376.80 and decreased by 4.72% from 376.80 to 342.10. The AIRs in men increased by 4.00% and decreased by 3.01%. The AIRs in women decreased by 2.18% and increased by 2.11% (CAT; p<0.01). The AIRs by region and income also showed trends of increase and decrease. CONCLUSION: The study showed that the incidence trend of SPE increased and decreased from 2014 to 2018. This result would be able to aid in the planning of public oral health, and may also serve as fundamental data for verifying the impact of the public oral health policies implemented.

Validation of the Korean Academy of Geriatric Dentistry screening questionnaire and oral frailty diagnostic criteria in community-dwelling older adults.

OBJECTIVES: This study aimed to establish the validity-specifically, the sensitivity and specificity-of the screening questionnaire and diagnostic criteria for oral frailty proposed by the Korean Academy of Geriatric Dentistry (KAGD) among community-dwelling older adults. METHODS: This study enrolled 100 participants. Among various definitions of oral frailty, this study used the criteria proposed by Tanaka as the reference test. The screening questionnaire consisted of 11 items for screening physical frailty, chewing ability, swallowing difficulties, oral dryness, and tongue and lip motor function. Each question had a different scoring weight, and if the total score was 1 or higher, an oral frailty diagnostic examination proposed by the KAGD would be recommended. The diagnostic test was the oral frailty diagnostic criteria proposed by the KAGD including 6 measures: chewing ability, occlusal force, tongue pressure, oral dryness, swallowing difficulty, and oral hygiene. If a participant exhibited 2 or more positive measures, this participant was classified as "oral frail." The screening questionnaire was analyzed using a cut-off value of 1 or higher, while the diagnostic criteria utilized a cut-off of 2 or more positive measures. Sensitivity and specificity were calculated. RESULTS: The screening questionnaire showed significant power for screening oral frailty (area under the receiver operating characteristic curve, 0.783; sensitivity, 87.8%; specificity, 52.5%). The diagnostic accuracy of the newly proposed diagnostic criteria was acceptable (sensitivity, 95.1%; specificity, 42.4%). CONCLUSIONS: The newly proposed screening questionnaire and diagnostic criteria in Korea appear to be a useful tool to identify oral frailty in community-dwelling older adults.

Anti-biofilm activity of a novel nanoemulsion containing Curcuma xanthorrhiza oil.

OBJECTIVES: We aimed to solubilize Curcuma xanthorrhiza oil (CXO) using nanoemulsification and evaluate its inhibitory effects against biofilm formation. METHODS: The components of CXO were evaluated through high-performance liquid chromatography (HPLC) analysis. Healthy human saliva was inoculated onto hydroxyapatite discs to form microcosm biofilms for four days and treated six times with each antimicrobial agent: distilled water (DW), CXO emulsion (EM), CXO nanoemulsion (NE), and positive controls (Listerine and chlorhexidine). Biofilm fluorescence imaging was performed using quantitative light-induced fluorescence, and cell viability and dry-weight measurements were obtained. We compared the bacterial cell and extracellular polysaccharide (EPS) biovolume and thickness using confocal laser scanning microscopy (CLSM). RESULTS: HPLC analysis revealed that CXO was composed of approximately 47% xanthorrhizol. Compared with DW, NE exhibited significantly lower red fluorescence intensity and area (42% and 37%, p < 0.001 and p < 0.001, respectively), and reduced total and aciduric bacterial cell viability (7.3% and 3.9%, p < 0.001, p = 0.01, respectively). Furthermore, the bacterial cell and EPS biovolume and thickness in NE decreased by 40-80% compared to DW, similar to chlorhexidine. Conversely, EM showed a significant difference only in cell viability against total bacteria when compared with DW (p = 0.003), with EPS biovolume and thickness exhibiting higher values than DW. CONCLUSIONS: Nanoemulsification successfully solubilized CXO and demonstrated superior anti-biofilm effects compared to the emulsion form. CLINICAL SIGNIFICANCE: These findings suggest the potential use of NE as a novel antimicrobial agent for preventing oral diseases.

Effectiveness of an Oral Health Education Program Using a Smart Toothbrush with Quantitative Light-Induced Fluorescence Technology in Children.

This randomized controlled trial aimed to educate patients and manage oral hygiene remotely via a smart toothbrush (ST) by using mobile applications and to improve oral hygiene and habits by evaluating the plaque state via images from a Q-ray cam, which is a quantitative light-induced fluorescence (QLF) digital imaging device. In total, 68 children (aged 6-12 years) were randomly divided into three groups. Group I was assigned an electro-toothbrush (ET), group II was assigned a smart toothbrush (ST), and group III used a manual toothbrush (MT). Each group used an assigned toothbrush and was checked after 1 and 3 months. Oral hygiene status was evaluated using the patient hygiene performance (PHP) index and fluorescent plaque index (FPI), which are presented in the QLF program. In addition, questionnaires on oral health behaviors and attitudes were also evaluated. There was a 0.24 decrease in the PHP index and a 1.40 decrease in the simple hygiene score three months later compared with the baseline in the ST group, with no significant difference between the three methods (p = 0.518, p = 0.626). Many group II participants said that ST helped with oral hygiene, and they were willing to use it continuously. In addition, all participants' brushing times and attitudes toward oral hygiene improved after oral hygiene education using a Q-ray cam. Therefore, the use of STs provided good dental health education and a plaque-decreasing effect to children aged 6-12 years old. Furthermore, the QLF device can be used as a useful tool for maintaining good oral hygiene in children.

Evaluation of the clinical efficacy of quantitative light-induced fluorescence technology in diagnosing cracked teeth.

BACKGROUND: This retrospective study evaluated the clinical efficacy of quantitative light-induced fluorescence (QLF) technology for crack detection and the diagnosis of cracked teeth and assessed the possibility of a quantitative evaluation of cracks using QLF technology. METHODS: Patients who were clinically diagnosed with cracked teeth over a 1-year period were included. The QLF images of the corresponding symptomatic cracked teeth and asymptomatic contralateral teeth with crack lines were taken with Qraypen C (AIOBIO, Seoul, Korea). Fluorescence loss (ΔF), maximum fluorescence loss (ΔFmax), red fluorescence (ΔR), and maximum red fluorescence (ΔRmax) of the crack line were analyzed. The correlation between these parameters and sex, age, tooth position (1st premolar, 2nd premolar, 1st molar, 2nd molar), spontaneous pain (+/-), percussion test (+/-), cold test (++/+/-), and bite test (+/-) were statistically analyzed. RESULTS: A total of 66 patients were included. Twenty-four patients had asymptomatic contralateral teeth with apparent crack lines; thus, 90 teeth were analyzed. The crack lines in 84 teeth observed as red fluorescent lines on the QLF images showed ΔR values higher than the cut-off value set by the analysis program used. The patient's age and the ∣ΔF∣ and ΔR values were positively correlated. However, there was no statistically significant difference in the QLF parameters between the same patient's symptomatic tooth and the contralateral tooth. CONCLUSIONS: QLF technology is a useful assistive diagnostic device for diagnosing cracked teeth.

Oral characteristics and dietary habits of preterm children: A retrospective study using National Health Screening Program for Infants and Children.

The rate of preterm birth is increasing worldwide and preterm infants are susceptible to oral health problems. Hence, this study aimed to investigate the effect of premature birth on dietary and oral characteristics as well as dental treatment experiences of preterm infants using a nationwide cohort study. Data was retrospectively analyzed from National Health Screening Program for Infants and Children (NHSIC) of the National Health Insurance Service of Korea. 5% sample of children born between 2008 and 2012 who completed first or second infant health screening were included and divided into full-term and preterm-birth groups. Clinical data variables such as dietary habits, oral characteristics, and dental treatment experiences were investigated and comparatively analyzed. Preterm infants showed significantly lower rates of breastfeeding at 4-6 months (p<0.001), delayed start of weaning food at 9-12 months (p<0.001), higher rates of bottle feeding at 18-24 months (p<0.001), poor appetite at 30-36 months (p<0.001) and higher rates of improper swallowing and chewing function at 42-53 months (p = 0.023) than full-term infants. Preterm infants also had eating habits leading to poor oral conditions and higher percentage of absence of dental visit compared to full-term infants (p = 0.036). However, dental treatments including 1-visit pulpectomy (p = 0.007) and 2-visit pulpectomy (p = 0.042) significantly decreased when oral health screening was completed at least once. The NHSIC can be an effective policy for oral health management in preterm infants.

Deep learning and clustering approaches for dental implant size classification based on periapical radiographs.

This study investigated two artificial intelligence (AI) methods for automatically classifying dental implant diameter and length based on periapical radiographs. The first method, deep learning (DL), involved utilizing the pre-trained VGG16 model and adjusting the fine-tuning degree to analyze image data obtained from periapical radiographs. The second method, clustering analysis, was accomplished by analyzing the implant-specific feature vector derived from three key points coordinates of the dental implant using the k-means++ algorithm and adjusting the weight of the feature vector. DL and clustering model classified dental implant size into nine groups. The performance metrics of AI models were accuracy, sensitivity, specificity, F1-score, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC-ROC). The final DL model yielded performances above 0.994, 0.950, 0.994, 0.974, 0.952, 0.994, and 0.975, respectively, and the final clustering model yielded performances above 0.983, 0.900, 0.988, 0.923, 0.909, 0.988, and 0.947, respectively. When comparing the AI model before tuning and the final AI model, statistically significant performance improvements were observed in six out of nine groups for DL models and four out of nine groups for clustering models based on AUC-ROC. Two AI models showed reliable classification performances. For clinical applications, AI models require validation on various multicenter data.

Prioritization of research engaged with rare disease stakeholders: a systematic review and thematic analysis.

BACKGROUND: Although rare diseases (RD) are increasingly becoming a priority for healthcare activities and services around the world, developing research policy for investigating RD in public settings proves challenging due to the limited nature of existing evidence. Rare conditions require the involvement of a wide range of stakeholders in order to promote general awareness and garner political support. Consequently, it is critically important to identify trends in the various types of research focusing on rare disease stakeholders, including the specific topics or issues to be included in surveys and studies focused on RD stakeholders. This systematic review and thematic analysis analyses the existing literature based on RD surveys, including the stakeholders involved, and proposes potential research priorities and initiatives for policy-making related to RD. METHODS: Articles were downloaded and analyzed from across five electronic databases (PubMed, EMBASE, Cochrane Central, Web of Science, and CINHAL) and 115 studies were included. RESULTS: Across 115 studies, the main research participants were patients and/or caregivers (n = 77, 67.0%), health professionals (n = 18, 15.7%), and the public (n = 7, 6.1%). The studies discussed RDs in general (n = 46, 40.0%), endocrine, nutritional, and metabolic diseases (n = 20, 17.4%) and other RDs. Experiences with RD were examined by more than half of the selected studies (n = 74, 64.3%), followed by the opinions of stakeholders (n = 24, 20.9%). Most of the studies used surveys in order to collect relevant data (n = 114, 99.1%). Additionally, the majority of the studies were conducted in high-income countries (n = 92, 80.0%) and rarely in middle and low-income countries (n = 12, 13.8%). CONCLUSION: Stakeholder research on RD reveals that there are significant instances of unmet needs and various challenges faced by the medical system in dealing with RDs. Furthermore, public awareness and support is critical to ensuring political feasibility of increasing national-level investments for RDs and development of medical products and treatment.

A novel model to predict tooth bleaching efficacy using autofluorescence of the tooth.

OBJECTIVES: We aimed to confirm whether autofluorescence emitted from teeth can predict tooth bleaching efficacy and establish a novel model combining natural color parameters and tooth autofluorescence data to improve the predictability of tooth bleaching. METHODS: A total of 61 tooth specimens were prepared from extracted human molars/premolars and immersed in 35% hydrogen peroxide for 1 h for tooth bleaching. The changes in laser-induced fluorescence (∆LIF) were assessed using Raman spectrometry. Tooth color and autofluorescence data were obtained using quantitative light-induced fluorescence (QLF) technology. Pearson correlation analyses were used to confirm the relationship between ∆LIF and autofluorescence. Intraclass correlation coefficients (ICC) were calculated to compare the conventional and new prediction models. Decision tree analysis was performed to evaluate clinical applicability. RESULTS: The yellowness-to-blueness value from fluorescence imaging showed a moderate correlation with ∆LIF (r= -0.409, p = 0.001). The degree of agreement between the actual efficacy and that predicted by our novel model was high (ICC=0.933, p = 0.002). Decision tree analysis suggested that tooth autofluorescence could be a key factor in prediction of tooth bleaching outcomes. CONCLUSIONS: Our findings showed that autofluorescence detected from QLF images may be used to predict tooth bleaching efficacy. Our proposed model appeared to improve the predictability of tooth bleaching.

Optical detection of oral biofilm in hospitalized geriatric patients using quantitative light-induced fluorescence technology.

Detection and removal of pathological oral biofilm are essential in hospitalized geriatric patients as the biofilm can lead to lung infection. However, as elderly patients often have cognitive and physical impairments, general oral examination is complicated and detection of pathological biofilms is challenging. Quantitative light-induced fluorescence (QLF) technology, which is currently actively used to detect bacterial structures in the oral cavity, is used to detect dental biofilm and to identify various oral bacterial infections. We confirmed the applicability of QLF technology to oral hygiene assessment and evaluation of hospitalized geriatric patients using the QLF technology to detect and remove the pathological oral biofilm in a hospitalized geriatric patient. The oral biofilm attached to the oral mucosa was difficult to observe with the naked eye. However, it was detected with red fluorescence on QLF images, which helped us observe the to detect pathological oral biofilm and evaluate the effectiveness of oral hygiene care (OHC). After OHC, the strong red fluorescence expressed in the oral mucosa was no longer observed. This change in the clinical aspect of red fluorescence suggests that QLF can be used to detect pathological oral biofilm accumulated on the oral mucous membrane and evaluate the effectiveness of OHC in hospitalized patients with extremely poor oral hygiene.