• Journal of Veterinary Clinics
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• v.32 no.1
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• pp.73-77
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• 2015

There has been increasing attention on sample size requirements in peer reviewed medical literatures. Accordingly, a statistically-valid sample size determination has been described for a variety of medical situations including diagnostic test accuracy studies. If the sample is too small, the estimate is too inaccurate to be useful. On the other hand, a very large sample size would yield the estimate with more accurate than required but may be costly and inefficient. Choosing the optimal sample size depends on statistical considerations, such as the desired precision, statistical power, confidence level and prevalence of disease, and non-statistical considerations, such as resources, cost and sample availability. In a previous paper (J Vet Clin 2012; 29: 68-77) we briefly described the statistical theory behind sample size calculations and provided practical methods of calculating sample size in different situations for different research purposes. This review describes how to calculate sample sizes when assessing diagnostic test performance such as sensitivity and specificity alone. Also included in this paper are tables and formulae to help researchers for designing diagnostic test studies and calculating sample size in studies evaluating test performance. For complex studies clinicians are encouraged to consult a statistician to help in the design and analysis for an accurate determination of the sample size.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.22 no.1
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• pp.1-10
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• 2018

Objectives The purpose of this study is to compare the representative differential diagnosis methods of blood stasis pattern used in Korea, China and Japan, and then to characterize each diagnostic method. Methods Through the journal databases, we have selected representative tools that were developed for differential diagnosis of blood stasis pattern in Korea, China and Japan. In order to characterize the selected check-lists or questionnaires, we investigated the number of items, contents, score calculation method, internal consistency, and accuracy of each selected tool. Results A total of four diagnostic tools were finally selected; quantitative diagnosis scale of blood stasis syndrome (QDSBSS), diagnostic criteria for blood stasis (DCBS), blood stasis questionnaire (BSQ), and blood stasis syndrome questionnaire (BSSQ). The key points in the differential diagnosis for blood stasis were different for each of the diagnostic tool. The key point was oral mucosa (including tongue) status in the QDSBSS. Meanwhile it was abdominal pain/resistance in the DCBS, and general pain in the BSQ. Accuracy of the QDSBSS, the BSQ and the BSSQ were powerful but all of them was not generalized. Conclusions Therefore, it is desirable to select and apply a plurality of appropriate tools according to the characteristics of the blood stasis patients.

• Journal of Biomedical Engineering Research
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• v.40 no.3
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• pp.97-104
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• 2019

To examine different types of influenza diagnostic test kits automatically, automated rapid influenza diagnostic test method based on image recognition is proposed in this paper. First, the proposed methods classify a variety of the rapid influenza diagnostic test kit based on support vector machine that analyzes the kits' feature point. Then, to improve the accuracy of test, the proposed methods match the histogram of both the target image of influenza kit and the input image of influenza kit for minimizing the effect of environment factors, such as lighting and exposure variations. And, to minimize the effect from composition of the hand-helds devices, the proposed methods extract the feature point and match point-by-point between target image of influenza kit and input image of influenza kit. Experimental results of 124 experimental group show that the proposed methods significantly have effectiveness, which shows 90% accuracy in moderate antigen, for the preliminary examination of influenza, and provides the opportunity for taking action against influenza.

• Journal of Biomedical Engineering Research
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• v.40 no.2
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• pp.48-54
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• 2019

This paper proposed a method of validation data augmentation for improving the grading accuracy of diabetic macular edema (DME) using deep learning. The data augmentation technique is basically applied in order to secure diversity of data by transforming one image to several images through random translation, rotation, scaling and reflection in preparation of input data of the deep neural network (DNN). In this paper, we apply this technique in the validation process of the trained DNN, and improve the grading accuracy by combining the classification results of the augmented images. To verify the effectiveness, 1,200 retinal images of Messidor dataset was divided into training and validation data at the ratio 7:3. By applying random augmentation to 359 validation data, $1.61{\pm}0.55%$ accuracy improvement was achieved in the case of six times augmentation (N=6). This simple method has shown that the accuracy can be improved in the N range from 2 to 6 with the correlation coefficient of 0.5667. Therefore, it is expected to help improve the diagnostic accuracy of DME with the grading information provided by the proposed DNN.

• The Journal of the Korean bone and joint tumor society
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• v.11 no.1
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• pp.32-39
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• 2005

Introduction: Currently, F-18 fluorodeoxyglucose positron emission tomography scans (FDG-PET) has been investigated in soft tissue tumor especially for tumor detection and noninvasive grading. However, the validity and the efficacy of FDG-PET are still unclear in clinical evaluation. The purpose of this study is to determine the efficacy of FDG-PET in compared to conventional diagnostic imaging studies currently used in the soft tissue tumor. Methods: Between March 2001 and March 2002, 29 patients (sixteen males, thirteen females, mean age, 47 years; a range from 4 to 73) diagnosed with soft tissue tumor were evaluated by both conventional diagnostic imaging and FDG-PET. Valid reference test of the local lesion was the histopathologic diagnosis, which was measured in all patients. The suspecting metastasis in the imaging studies was validated by pathology or follow up imaging for at least 6 months. Each imaging diagnosis was made independently. The accuracy of each diagnostic method was evaluated. The incremental cost accuracy ratio was determined in each diagnostic method. Results: For detection of local lesion, sensitivity, specificity, and accuracy for MRI and FDGPET scans were 91%, 57%, 83% and 95%, 43%, 83% respectively. For detection of distant lesion, sensitivity, specificity, accuracy for conventional diagnostic methods and FDG-PET scans were 77%, 89%, 87% and 92%, 94%, 93% respectively. The incremental cost accuracy ratio (ICAR) of FDG-PET for detection of distant lesion was 145,000won/%. According to ICAR for each tumor grade, PET strategy is most cost-effective at high grade tumors. Conclusions: For detection of local lesion such as recurrence or remnant tumor, FDG-PET scan was not more accurate than MRI. However, It was more accurate for detection of metastatic lesion than conventional methods. For detection of high grade tumor, PET was most costeffective than for detection of lower grade tumor.

• The Korean Journal of Cytopathology
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• v.19 no.2
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• pp.111-118
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• 2008

Background : Cervicovaginal cytology is a screening test of uterine cervical cancer. The sensitivity of cervicovaginal cytology is less than 50%, but studies of cytologic/histologic correlation are limited. We analyzed the diagnostic accuracy of cervicovaginal cytology in the detection of the squamous epithelial lesions of the uterine cervix and investigate the cause of diagnostic discordance. Materials and Methods : We collected a total of 481 sets of cervicovaginal cytology and biopsies over 5 years. The cytologic diagnoses were categorized based on The Bethesda System and the histologic diagnoses were classified as negative, flat condyloma, cervical intraepithelial neoplasia (CIN) I, CIN II, CIN III, or squamous cell carcinoma. Cytohistologic discrepancies were reviewed. Results: The concordance rate between the cytological and the histological diagnosis was 79.0%. The sensitivity and specificity of cervicovaginal cytology were 80.6% and 92.6%, respectively. Its positive predictive value and negative predictive value were 93.7% and 77.7%, respectively. The false negative rate was 19.4%. Among 54 false negative cytology cases, they were confirmed by histology as 50 flat condylomas, 2 CIN I, 1 CIN III, and 1 squamous cell carcinoma. The causes of false negative cytology were sampling errors in 75.6% and interpretation errors in 24.4%. The false positive rate was 7.4%. Among 15 false positive cytology cases, they were confirmed by histology as 12 atypical squamous cells of undetermined significance (ASCUS) and 3 low grade squamous intraepithelial lesions (LSIL). The cause of error was interpretation error in all cases. The overall diagnostic accuracy of cervicovaginal cytology was 85.7%. Conclusions : Cervicovaginal cytology shows high overall diagnostic accuracy and is a useful primary screen of uterine cervical cancer.

• 대한핵의학회:학술대회논문집
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• 1973.11a
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• pp.49.2-49.2
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• 1973

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.4
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• pp.1583-1588
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• 2012

Fine needle aspiration (FNA) cytology is well accepted as a safe, reliable, minimal invasive and cost-effective method for diagnosis of salivary gland lesions. This study evaluated the accuracy and diagnostic performance of FNA cytology in Thailand. A consecutive series of 290 samples from 246 patients during January 2001-December 2009 were evaluated from the archive of the Anatomical Pathology Department of our institution and 133 specimens were verified by histopathologic diagnoses, obtained with material from surgical excision or biopsy. Cytologic diagnoses classified as unsatisfactory, benign, suspicious for malignancy and malignant were compared with the histopathological findings. Among the 133 satisfactory specimens, the anatomic sites were 70 (52.6%) parotid glands and 63 (47.4 %) submandibular glands. FNA cytological diagnoses showed benign lesions in 119 cases (89.5 %), suspicious for malignancy in 3 cases (2.2 %) and malignant in 11 cases (8.3%). From the subsequent histopathologic diagnoses, 3/133 cases of benign cytology turned out to be malignant lesions, the false negative rate being 2.2 % and 1/133 case of malignant cytology turned out to be a benign lesion, giving a false positive rate was 0.8%. The overall accuracy, sensitivity, specificity, positive predictive value and negative predictive value were 97.0% (95% CI, 70.6%-99.4%), 81.3% (95% CI, 54.4%-96.0%), 99.1% (95% CI, 95.4%-100%), 92.9% (95% CI, 66.1%-99.8), 97.5% (95% CI, 92.8%-99.5%), respectively. This study indicated that FNA cytology of salivary gland is a reliable and highly accurate diagnostic method for diagnosis of salivary gland lesions. It not only provides preoperative diagnosis for therapeutic management but also can prevent unnecessary surgery.

• Investigative Magnetic Resonance Imaging
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• v.1 no.1
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• pp.148-153
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• 1997

Purpose: To evaluate the diagnostic role of a three-dimensional MR cholangiopancreatography (MRCP) over endoscopic retrograde cholangio-pancreatography (ERCP) in various extrah-epatic biliary disease. Materials and Methods: MRCP and ERCP were performed in 45 consecutive patients with suspected extrahepatic biliary diseases. MRCP was obtained using a reverse fast imaging with a steady-state free precession (reverse FISP: PSIF) sequence, and then images were reconstructed by standard MIP algorithm. The predictability of biliary dilatation and level of obstruction of MRCP was evaluated using ERCP as a gold standard. The accuracy distinguishing malignant from benign lesions, and overall diagnostic accuracy were compared between MRCP and ERCP. Results: The sensitivity, specificity and accuracy of MRCP in predicting biliary dilatation were 94.6%, 75.0% and 91.1%, respectively. The level of obstruction was accurate in 87.0% with MRCP. The sensitivity, specificity and accuracy of MRCP and ERCP in distinguishing malignant from benign lesions were 76.2%, 87.5% and 82.2% and 71.4%, 83.3% and 77.8%, respectively. The overall diagnostic accuracy was 60.0% with MRCP and 55.6% with ERCP. Conclusion: 3D MRCP shows a good diagnostic value compared to that of ERCP, and can replace a ERCP.

• Journal of Genetic Medicine
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• v.8 no.1
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• pp.28-34
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• 2011

Most clinicians understand clinical trials as the evaluation process for new medicine before their use. However, clinical trials can also be applied to laboratory diagnostic tests (LDTs) to verify diagnostic accuracy and efficacy before their clinical laboratory implementation for patients. The clinical trial of LDT has two distinctive characteristics that are different from the case of pharmaceuticals and thus worth special consideration. One of them is the level of evidence. The well-designed randomized controlled trials (RCTs) are known to provide the best evidence to prove the clinical efficacy of any pharmaceutical products. However, RCTs lose practicality when applied to LDTs due to various issues including ethical complications. For this reason, comparative study format is considered more feasible approach for LDTs. In addition pharmaceuticals and LDTs are different in that the user's intervention is not required for the former but critical to the latter. Moreover, in the case of pharmaceuticals, end-products are produced by manufacturers before being used by clinicians. However, in LDTs, once reagents and instruments are provided by manufacturers, they are first utilized by clinical laboratories to produce test results in order for clinicians to use them later. In other words, when it comes to LDTs, clinical laboratories play the role of manufacturers, providing reliable test results with improved quality assurance. Considering the distinctive characteristics of LDTs, we would like to offer detailed suggestions to successfully perform clinical trials in LDTs, which include analytical performance measures, clinical test performance measures, diagnostic test accuracy measures, clinical effectiveness measures, and post-implementation surveillance.