Ji, Sumin;Yang, Yeseul;Jeong, Yeji;Hwang, Sung-Hyun;Kim, Myung-Chul;Kim, Yongbaek
Journal of Veterinary Science
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v.22
no.1
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pp.14.1-14.11
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2021
Background: Quantitation of urine protein is important in dogs with chronic kidney disease. Various analyzers are used to measure urine protein-to-creatinine ratios (UPCR). Objectives: This study aimed to compare the UPCR obtained by three types of analyzers (automated wet chemistry analyzer, in-house dry chemistry analyzer, and dipstick reading device) and investigate whether the differences could affect clinical decision process. Methods: Urine samples were collected from 115 dogs. UPCR values were obtained using three analyzers. Bland-Altman and Passing Bablok tests were used to analyze agreement between the UPCR values. Urine samples were classified as normal or proteinuria based on the UPCR values obtained by each analyzer and concordance in the classification evaluated with Cohen's kappa coefficient. Results: Passing and Bablok regression showed that there were proportional as well as constant difference between UPCR values obtained by a dipstick reading device and those obtained by the other analyzers. The concordance in the classification of proteinuria was very high (κ = 0.82) between the automated wet chemistry analyzer and in-house dry chemistry analyzer, while the dipstick reading device showed moderate concordance with the automated wet chemistry analyzer (κ = 0.52) and in-house dry chemistry analyzer (κ = 0.53). Conclusions: Although the urine dipstick test is simple and a widely used point-of-care test, our results indicate that UPCR values obtained by the dipstick test are not appropriate for clinical use. Inter-instrumental variability may affect clinical decision process based on UPCR values and should be emphasized in veterinary practice.
Kyungjin Lee;Seo-Yul Kim;Kyeong-Mee Park;Sujin Yang;Kee-Deog Kim;Wonse Park
Journal of Dental Anesthesia and Pain Medicine
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v.23
no.1
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pp.9-17
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2023
Background: Dental evaluation and protection are important for preventing traumatic dental injuries when patients are under general anesthesia. The objective of the present study was to develop a questionnaire based on dentition-related risk factors that could serve as a valuable tool for dental evaluation and documentation. Methods: We developed a questionnaire for dental evaluation before administration of general anesthesia, investigated the association between patient-and-dentist responses and mouthguard fabrication, and assessed response agreement between 100 patients. Results: Protective mouthguards were fabricated for 27 patients who were identified as having a high risk of dental injury. There was a strong association between dentists' responses and mouthguard fabrication, depending on the general oral health status, use of ceramic prosthesis, presence of masticatory pain related to periodontal diseases, gingival edema, and implants (P < 0.05). Response agreement between patients and dentists for items related to dental pain, loss of dental pulp vitality, root canal therapy, dental trauma, aesthetic prosthesis, tooth mobility, and implant prosthesis was high (Cohen's kappa coefficient κ ≥ 0.6). Conclusions: A high agreement was observed between patient-dentist responses and a strong association with mouthguard fabrication for items pertaining to ceramic prosthesis, masticatory pain, and dental implants. Patients with a "yes" response to these items are recommended to undergo a dental evaluation and use a dental protective device while under general anesthesia.
Crop classification is very important for estimating crop yield and figuring out accurate cultivation area. The purpose of this study is to classify crops harvested in fall in Idam-ri, Goesan-gun, Chungcheongbuk-do by using unmanned aerial vehicle (UAV) images and support vector machine (SVM) model. The study proceeded in the order of image acquisition, variable extraction, model building, and evaluation. First, RGB and multispectral image were acquired on September 13, 2021. Independent variables which were applied to Farm-Map, consisted gray level co-occurrence matrix (GLCM)-based texture characteristics by using RGB images, and multispectral reflectance data. The crop classification model was built using texture characteristics and reflectance data, and finally, accuracy evaluation was performed using the error matrix. As a result of the study, the classification model consisted of four types to compare the classification accuracy according to the combination of independent variables. The result of four types of model analysis, recursive feature elimination (RFE) model showed the highest accuracy with an overall accuracy (OA) of 88.64%, Kappa coefficient of 0.84. UAV-based RGB and multispectral images effectively classified cabbage, rice and soybean when the SVM model was applied. The results of this study provided capacity usefully in classifying crops using single-period images. These technologies are expected to improve the accuracy and efficiency of crop cultivation area surveys by supplementing additional data learning, and to provide basic data for estimating crop yields.
Crop classification plays a vitalrole in monitoring agricultural landscapes and enhancing food production. In this study, we explore the effectiveness of Long Short-Term Memory (LSTM) models for crop classification, focusing on distinguishing between apple and rice crops. The aim wasto overcome the challenges associatedwith finding phenology-based classification thresholds by utilizing LSTM to capture the entire Normalized Difference Vegetation Index (NDVI)trend. Our methodology involvestraining the LSTM model using a reference site and applying it to three separate three test sites. Firstly, we generated 25 NDVI imagesfrom the Sentinel-2A data. Aftersegmenting study areas, we calculated the mean NDVI values for each segment. For the reference area, employed a training approach utilizing the NDVI trend line. This trend line served as the basis for training our crop classification model. Following the training phase, we applied the trained model to three separate test sites. The results demonstrated a high overall accuracy of 0.92 and a kappa coefficient of 0.85 for the reference site. The overall accuracies for the test sites were also favorable, ranging from 0.88 to 0.92, indicating successful classification outcomes. We also found that certain phenological metrics can be less effective in crop classification therefore limitations of relying solely on phenological map thresholds and emphasizes the challenges in detecting phenology in real-time, particularly in the early stages of crops. Our study demonstrates the potential of LSTM models in crop classification tasks, showcasing their ability to capture temporal dependencies and analyze timeseriesremote sensing data.While limitations exist in capturing specific phenological events, the integration of alternative approaches holds promise for enhancing classification accuracy. By leveraging advanced techniques and considering the specific challenges of agricultural landscapes, we can continue to refine crop classification models and support agricultural management practices.
Purpose: This study assessed the diagnostic performance of stitched and non-stitched cross-sectional cone-beam computed tomography (CBCT) images of non-displaced ovine mandibular fractures. Materials and Methods: In this ex vivo study, non-displaced fractures were artificially created in 10 ovine mandibles (20 hemi-mandibles) using a hammer. The control group comprised 8 hemi-mandibles. The non-displaced fracture lines were oblique or vertical, <0.5 mm wide, 10-20 mm long, and only in the buccal or lingual cortex. Fracture lines in the ramus and posterior mandible were created to be at the interface or borders of the 2 stitched images. CBCT images were obtained from the specimens with an 80 mm×80 mm field of view before and after fracture induction. OnDemand software (Cybermed, Seoul, Korea) was used for stitching the CBCT images. Four observers evaluated 56 (28 stitched and 28 non-stitched) images to detect fracture lines. The diagnostic performance of stitched and non-stitched images was assessed by calculating the area under the receiver operating characteristic curve (AUC). Sensitivity and specificity values were also calculated (alpha=0.05). Results: The AUC was calculated to be 0.862 and 0.825 for the stitched and non-stitched images, respectively (P=0.747). The sensitivity and specificity were 90% and 75% for the non-stitched images and 85% and 87% for the stitched images, respectively. The inter-observer reliability was shown by a Fleiss kappa coefficient of 0.79, indicating good agreement. Conclusion: No significant difference was found in the diagnostic performance of stitched and non-stitched cross-sectional CBCT images of non-displaced fractures of the ovine mandible.
Among the commonly known tools to diagnose diabetes are fasting plasma glucose (FPG), HbA1c., and OGTT known as gold standard. However, there can be many disagreements on the ways to diagnose diabetes. In this study, we examined the differences of the types of diabetes according to the applicability of FPG and HbA1c. Moreover, we evaluated the concordance of diagnosis. We excluded subjects with missing glucose and HbA1c data, as well as those previously diagnosed with diabetes, and those who fasted less than 8 hours. The data of 4,502 subjects (1,956 men and 2,546 women) from the 2015 KNHNES were analyzed. We divided these patients into three categories which are normal, prediabetes, and diabetes, based on the FPG and HbA1c. In men, the number of subjects with FPG ranging from 100 to 125 mg/dL and HbA1c ${\geq}6.5%$ was 23 out of 664, and the number of subjects with FPG < 126 mg/dL and HbA1c ${\geq}6.5%$ was 39 out of 86 newly diagnosed diabetes patients. The concordance rate was as follows: Normal 80.3%, prediabetes 44.9%, and diabetes 54.7%. The coefficient of Cohen's Kappa was 0.322 in men and 0.362 in women; this suggests that both gender showed a low concordance rate. However, when we divided them into two categories (nondiabetes and diabetes), Kappa was 0.582 in men and 0.637 in women, showing a relatively high concordance rate. While all subjects with FPG ${\geq}126mg/dL$ showed a significantly high HOMA IR, all subjects with FPG < 126 mg/dL showed a significantly high QUICKI. Considering the low concordance rate for the diagnosis of diabetes and characteristic of diagnostic tests, it is necessary to combine the related tests for diagnosing diabetes.
Early diagnosis for upper facial trauma is difficult by using the standard Water's view (S-Water's) in general radiograph due to overlapping of anatomical structures, the uncertainty of patient positioning, and specific patients with obese, pediatric, old, or high-risk. The purpose of this study was to analyze appropriate exposure angles through a comparison of two different protocols (S-Water's vs. reverse Water's view (R-Water's)) by using a head phantom. A head phantom and general radiograph with 75 kVp, 400 mA, 45 ms 18 mAs, and SID 100 cm. Images of R-Water's were obtained by different angles in the range of $0^{\circ}$ to $50^{\circ}$, which adjusted an angle at 1 degree interval in supine position. Survey elements were developed and three observers were evaluated with four elements including the maxillary sinus, zygomatic arch, petrous ridge, and image distortion. Statistical significant analysis were used the Krippendorff's alpha and Fleiss' kappa. The intra-class correlation (ICC) coefficient for three observers were high with maxillary, 0.957 (0.903, 0.995); zygomatic arch, 0.939 (0.866, 0.987); petrous ridge, 0.972 (0.897, 1.000); and image distortion, 0.949 (0.830, 1.000). The high-quality image (HI) and perfect agreement (PA) for acquired exposure angles were high in range of the maxillary sinus ($36^{\circ}-44^{\circ}C$), zygomatic arch ($33^{\circ}-40^{\circ}$), petrous ridge ($32^{\circ}-50^{\circ}$), and image distortion ($44^{\circ}-50^{\circ}$). Consequently, an appropriate exposure angles for the R-Water's view in the supine position for patients with facial trauma are in the from $36^{\circ}$ to $40^{\circ}$ in this phantom study. The results of this study will be helpful for the rapid diagnosis of facial fractures by simple radiography.
Park, Jae Seok;Choi, Won-Il;Min, Bo Ram;Park, Jie Hae;Chae, Jin Nyeong;Jeon, Young June;Yu, Ho Jung;Kim, Ji-Young;Kim, Gyoung-Ju;Ko, Sung-Min
Tuberculosis and Respiratory Diseases
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v.64
no.4
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pp.266-271
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2008
Background: Estimation of the probability of a patient having an acute pulmonary embolism (PE) for patients with a suspected PE are well established in North America and Europe. However, an assessment of the prediction rules for a PE has not been clearly defined in Korea. The aim of this study is to assess the prediction rules for patients with a suspected PE in Korea. Methods: We performed a retrospective study of 210 inpatients or patients that visited the emergency ward with a suspected PE where computed tomography pulmonary angiography was performed at a single institution between January 2005 and March 2007. Simplified Wells rules and revised Geneva rules were used to estimate the clinical probability of a PE based on information from medical records. Results: Of the 210 patients with a suspected PE, 49 (19.5%) patients had an actual diagnosis of a PE. The proportion of patients classified by Wells rules and the Geneva rules had a low probability of 1% and 21%, an intermediate probability of 62.5% and 76.2%, and a high probability of 33.8% and 2.8%, respectively. The prevalence of PE patients with a low, intermediate and high probability categorized by the Wells rules and Geneva rules was 100% and 4.5% in the low range, 18.2% and 22.5% in the intermediate range, and 19.7% and 50% in the high range, respectively. Receiver operating characteristic curve analysis showed that the revised Geneva rules had a higher accuracy than the Wells rules in terms of detecting PE. Concordance between the two prediction rules was poor ($\kappa$ coefficient=0.06). Conclusion: In the present study, the two prediction rules had a different predictive accuracy for pulmonary embolisms. Applying the revised Geneva rules to inpatients and emergency ward patients suspected of having PE may allow a more effective diagnostic process than the use of the Wells rules.
Korean Journal of Agricultural and Forest Meteorology
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v.23
no.1
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pp.15-33
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2021
In this study, the possibility of discriminating Fire blight (FB) infection tested using the hyperspectral imagery. The reflectance of healthy and infected leaves and branches was acquired with 5 nm of full width at high maximum (FWHM) and then it was standardized to 10 nm, 25 nm, 50 nm, and 80 nm of FWHM. The standardized samples were divided into training and test sets at ratios of 7:3, 5:5 and 3:7 to find the optimal bands of FWHM by the decision tree analysis. Classification accuracy was evaluated using overall accuracy (OA) and kappa coefficient (KC). The hyperspectral reflectance of infected leaves and branches was significantly lower than those of healthy green, red-edge (RE) and near infrared (NIR) regions. The bands selected for the first node were generally 750 and 800 nm; these were used to identify the infection of leaves and branches, respectively. The accuracy of the classifier was higher in the 7:3 ratio. Four bands with 50 nm of FWHM (450, 650, 750, and 950 nm) might be reasonable because the difference in the recalculated accuracy between 8 bands with 10 nm of FWHM (440, 580, 640, 660, 680, 710, 730, and 740 nm) and 4 bands was only 1.8% for OA and 4.1% for KC, respectively. Finally, adding two bands (550 nm and 800 nm with 25 nm of FWHM) in four bands with 50 nm of FWHM have been proposed to improve the usability of multispectral image sensors with performing various roles in agriculture as well as detecting FB with other combinations of spectral bands.
Journal of the korean academy of Pediatric Dentistry
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v.48
no.4
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pp.437-448
/
2021
The purpose of this study is to analyze morphological characteristics of maxillary primary molar's root and root canal. 268 children aged 3 - 7 years (175 boys, 93 girls) who had CBCT (152 children) and 3D CT (116 children) taken in Seoul National University Dental Hospital from January 2006 to April 2020 were included. The number of roots and root canals were analyzed in 1002 teeth without any root resorption or periapical pathologies. Curvature, angulation, length of root and root canal, as well as cross-sectional shapes of the root canal were analyzed in 218 teeth. By using Mimics and 3-Matics software, volume, surface area, and volume ratio of root canal was analyzed in 48 teeth. More than half of maxillary primary molars have 3 roots and 3 root canals. The degree of symmetry of root canal type was about 0.63 (Cohen's kappa coefficient). The most frequent shape of roots and canals was linear in 1st primary molars and curved in 2nd primary molars. Angulation, length of root and root canals was the largest on palatal roots. Most teeth showed ovoid or round shapes at apex. The largest root canal volume, surface area, volume ratio was found in the palatal roots.
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