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1.
Journal of Korean Academy of Oral Health ; : 210-216, 2019.
Article in English | WPRIM | ID: wpr-786019

ABSTRACT

OBJECTIVES: The primary objective of this study was to determine if the number of missing teeth could be predicted by oral disease pathogens, and the secondary objective was to assess whether deep learning is a better way of predicting the number of missing teeth than multivariable linear regression (MLR).METHODS: Data were collected through review of patient’s initial medical records. A total of 960 participants were cross-sectionally surveyed. MLR analysis was performed to assess the relationship between the number of missing teeth and the results of real-time PCR assay (done for quantification of 11 oral disease pathogens). A convolutional neural network (CNN) was used as the deep learning model and compared with MLR models. Each model was performed five times to generate an average accuracy rate and mean square error (MSE). The accuracy of predicting the number of missing teeth was evaluated and compared between the CNN and MLR methods.RESULTS: Model 1 had the demographic information necessary for the prediction of periodontal diseases in addition to the red and the orange complex bacteria that are highly predominant in oral diseases. The accuracy of the convolutional neural network in this model was 65.0%. However, applying Model 4, which added yellow complex bacteria to the total bacterial load, increased the expected extractions of dental caries to 70.2%.On the other hand, the accuracy of the MLR was about 50.0% in all models. The mean square error of the CNN was considerably smaller than that of the MLR, resulting in better predictability.CONCLUSIONS: Oral disease pathogens can be used as a predictor of missing teeth and deep learning can be a more accurate analysis method to predict the number of missing teeth as compared to MLR.


Subject(s)
Bacteria , Bacterial Load , Citrus sinensis , Dental Caries , Hand , Learning , Linear Models , Medical Records , Methods , Periodontal Diseases , Periodontitis , Pilot Projects , Real-Time Polymerase Chain Reaction , Tooth
2.
The Journal of Korean Academy of Prosthodontics ; : 27-32, 2013.
Article in Korean | WPRIM | ID: wpr-87090

ABSTRACT

PURPOSE: The aims of this study were to evaluate the effect of a resin coating on the shear bond strength of indirect composite restoration bonded to dentin with a self adhesive resin cement and to compare the shear bond strength with that of a conventional resin cement. MATERIALS AND METHODS: The occlusal enamels of thirty six extracted non-carious human molars were removed until the dentin flat surfaces of the teeth were exposed. Then, they were divided into 3 groups. The dentin surfaces of group 1 and 3 were left without any conditioning, while the dentin surfaces of group 2 were resin-coated with Clearfil SE bond and a flowable resin composite, Metafil Flo. After all specimens were temporized for 24 hours, indirect composite resin blocks fabricated by Tescera were bonded to dentins by Unicem for group 1 and 2, and by Panavia F for group 3. After 48 hours of water storage, shear bond strengths were measured. The data was analyzed with one-way analysis of variance and multiple comparison test (Tukey method). RESULTS: The shear bond strengths of Unicem applied to resin coated dentin surfaces were significantly higher than those of Unicem and Panavia F used to uncoated dentin surfaces (P<.0001). CONCLUSION: Application of a resin coating to the dentin surface significantly improved the shear bonding strength of a self adhesive resin cement in indirect restoration.


Subject(s)
Humans , Adhesives , Composite Resins , Dental Enamel , Dentin , Molar , Resin Cements , Tooth , Water
3.
Korean Journal of Medicine ; : 613-618, 2012.
Article in Korean | WPRIM | ID: wpr-85861

ABSTRACT

Superior mesenteric artery (SMA) syndrome is an uncommon cause of a proximal intestinal obstruction. The most characteristic symptoms are postprandial fullness, nausea, and vomiting. The diagnosis is established by ultrasonography and contrast-enhanced computed tomography. Almost all patients respond well to conservative management. However, if conservative management fails, surgical options should be applied. In this article, we report a case of SMA syndrome with Nutcracker syndrome in a patient with diabetes mellitus. Establishing the diagnosis of Nutcracker syndrome is usually based on clinical suspicion and radiological findings. Several complications that have been reported to result from SMA syndrome include peptic ulcer disease, pancreatitis, metabolic alkalosis, and uremic syndrome. However, Nutcracker syndrome accompanied by SMA syndrome is extremely uncommon, as described in this case. To our knowledge, this association has not been reported previously.


Subject(s)
Humans , Alkalosis , Diabetes Mellitus , Diabetes Mellitus, Type 1 , Intestinal Obstruction , Mesenteric Artery, Superior , Nausea , Pancreatitis , Peptic Ulcer , Superior Mesenteric Artery Syndrome , Vomiting
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