• Asian Pacific Journal of Cancer Prevention
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• 제14권1호
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• pp.31-37
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• 2013

Background: Throughout Indonesia, thyroid cancer is one of the ten commonest malignancies, with papillary thyroid carcinoma (PTC) in our hospital accounting for about 60% of all thyroid nodules. Although fine needle aspiration biopsy (FNAB) is the most reliable diagnostic tool, some nodules are diagnosed as indeterminate and second surgery is common for PTC. The aim of this study was to establish the diagnostic value and feasibility of testing the BRAF T1799A mutation on FNA specimens for improving PTC diagnosis. Materials and Methods: This prospective study enrolled 95 patients with thyroid nodules and future surgery planned. Results of mutational status were compared with surgical pathology diagnosis. Results: Of the 70 cases included in the final analysis, 62.8% were PTC and the prevalence of BRAF mutation was 38.6%. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for BRAF mutation analysis were 36%, 100%, 100% and 48%, respectively. With other data findings, nodules with "onset less than 5 year" and "hard consistency" were proven as diagnostic determinants for BRAF mutation with a probability of 62.5%. This mutation was also a significant risk factor for extra-capsular extension. Conclusions: Molecular analysis of the BRAF T1799A mutation in FNAB specimens has high specificity and positive predictive value for PTC. It could be used in the selective patients with clinical characteristics to facilitate PTC diagnosis and for guidance regarding extent of thyroidectomy.

• Journal of Periodontal and Implant Science
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• 제48권2호
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• pp.114-123
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• 2018

Purpose: The aim of the current study was to develop a computer-assisted detection system based on a deep convolutional neural network (CNN) algorithm and to evaluate the potential usefulness and accuracy of this system for the diagnosis and prediction of periodontally compromised teeth (PCT). Methods: Combining pretrained deep CNN architecture and a self-trained network, periapical radiographic images were used to determine the optimal CNN algorithm and weights. The diagnostic and predictive accuracy, sensitivity, specificity, positive predictive value, negative predictive value, receiver operating characteristic (ROC) curve, area under the ROC curve, confusion matrix, and 95% confidence intervals (CIs) were calculated using our deep CNN algorithm, based on a Keras framework in Python. Results: The periapical radiographic dataset was split into training (n=1,044), validation (n=348), and test (n=348) datasets. With the deep learning algorithm, the diagnostic accuracy for PCT was 81.0% for premolars and 76.7% for molars. Using 64 premolars and 64 molars that were clinically diagnosed as severe PCT, the accuracy of predicting extraction was 82.8% (95% CI, 70.1%-91.2%) for premolars and 73.4% (95% CI, 59.9%-84.0%) for molars. Conclusions: We demonstrated that the deep CNN algorithm was useful for assessing the diagnosis and predictability of PCT. Therefore, with further optimization of the PCT dataset and improvements in the algorithm, a computer-aided detection system can be expected to become an effective and efficient method of diagnosing and predicting PCT.

• Asian Pacific Journal of Cancer Prevention
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• 제16권1호
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• pp.345-349
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• 2015

Background: To determine the cut-off values of the preoperative risk of malignancy index (RMI) used in differentiating benign or malignant adnexal masses and to determine their significance in differential diagnosis by comparison of different systems. Materials and Methods: 191 operated women were assessed retrospectively. RMI of 1, 2, 3 and 4; cut-off values for an effective benign or malignant differentiation together with sensitivity, specificity, negative and positive predictive values were calculated. Results: Cut-off value for RMI 1 was found to be 250; there was significant (p<0.001) compatibility at this level with sensitivity of 60%, positive predictive value (PPV) of 75%, specificity of 93%, negative predictive value (NPV) of 88% and an overall compliance rate of 85%. When RMI 2 and 3 was obtained with a cut-off value of 200, there was significant (p<0.001) compatibility at this level for RMI 2 with sensitivity of 67%, PPV of 67%, specificity of 89%, NPV of 89%, histopathologic correlation of 84% while RMI 3 had significant (p<0.001) compatibility at the same level with sensitivity of 63%, PPV of 69%, specificity of 91%, NPV of 88% and a histopathologic correlation of 84%. Significant (p<0.001) compatibility for RMI 4 with a sensitivity of 67%, PPV of 73%, specificity of 92%, NPV of 89% and a histopathologic correlation of 86% was obtained at the cut-off level 400. Conclusions: RMI have a significant predictability in differentiating benign and malignant adnexal masses, thus can effectively be used in clinical practice.

• 전기학회논문지
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• 제59권10호
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• pp.1882-1888
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• 2010

It is widely known that ESA(Electric Signature Analysis) method is very useful one for fault diagnosis of an induction motor. Online fault diagnosis system of induction motors using LabVIEW is proposed to detect the fault of broken rotor bars and shorted turns in stator. This system is not model-based system of induction motor but LabVIEW-based fault diagnosis system using FFT spectrum of stator current in faulty motor without estimating of motor parameters. FFT of stator current in faulty induction motor is measured and compared with various reference fault data in data base to diagnose the fault. This paper is focused on to predict and diagnose of the health state of induction motors in steady state. Also, it can be given to motor operator and maintenance team in order to enhance an availability and maintainability of induction motors. Experimental results are demonstrated that the proposed system is very useful to diagnose the fault and to implement the predictive maintenance of induction motors.

• 유공압시스템학회논문집
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• 제1권2호
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• pp.1-7
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• 2004

In-process diagnosis is essential to achieve predictive maintenance in industrial plants. An in- process diagnosis method was proposed for hydraulic servo systems, which was based upon leakage flow measurement. Leakage due to servovalve wear was analysed and modeled mathematically far computer simulation work. The key idea of diagnosis algorithm is that when monitoring signals, such as servovalve input and load displacement are in steady states, the return-line flow of hydraulic servo systems can be regarded as null-leakage of servovalve. Virtual experiments were performed to ensure effectiveness of the proposed diagnosis method.

• 한국콘텐츠학회논문지
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• 제11권10호
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• pp.342-348
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• 2011

생체 간이식 공여자를 대상으로 시행되는 간생검 조직소견의 지방변성 정도와 복부초음파검사 결과를 분석하여, 지방간 질환의 진단에 있어서 초음파검사의 타당성을 알아보고자 하였다. 총 지방 함유량 10% 기준으로 범주화 하여 10% 이하를 음성, 10% 이상을 양성으로 하였을 때 초음파검사의 민감도는 64.6%이었고, 특이도는 68% 이었으며, 양성 예측도와 음성 예측도는 각각 76.8%, 54% 이었다. 초음파검사 결과 정상과 경증을 음성으로, 중등도를 양성으로 조작하였을 때 초음파검사의 민감도는 26.8% 이었고, 특이도는 100% 이었으며, 양성 예측도와 음성 예측도는 각각 100%, 45.5% 이었다. 총 지방 함유량 10% 이상을 상태변수(State variable)로 ROC curve 분석을 시행 하였을 때. 간/신장 명도비의 곡선하면적(Area under curve, AUC)은 0.859로 지방간을 예측하는데 좋은 지표로 나타났으며, 95% 신뢰구간(CI: 0.795~0.922)이 통계적으로 유의한 값을 보였다(p<0.001). 지방간진단에 있어서 복부초음파검사는 간생검 병리학적 결과를 예측하는데 높은 타당도를 보였다.

• Asian Pacific Journal of Cancer Prevention
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• 제13권8호
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• pp.3611-3615
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• 2012

Objective: The objective of this study was to establish the diagnostic accuracy, specificity and sensitivity of fine needle aspiration cytology(FNAC) for intra-oral tumors, comparing with histopathology as the gold standard. Materials and methods: Forty cases of FNA cytology from intraoral tumors was performed in AFID along with the demographic data and clinical information and then diagnosed at AFIP, Rawalpindi. Then the cytology results obtained per FNAC were compared with the histopathological biopsy results of the same lesions. The following variables were recorded for each patient: Age, gender, site of biopsy, diagnosis. The data were entered and analyzed using Open-epi version 2.0. Diagnostic accuracy, sensitivity, specificity, positive predictive value and negative predictive value were calculated. Cohen Kappa was further applied to compare the agreement between the biopsy and FNAC diagnoses. A p-value of < 0.05 was considered as statistically significant. Results: Among the total patients included in the study there were 24 males and 16 females, with a ratio of 1.5:1. Age of the patients ranged from 24 to 80 years with a mean of 52 years. A total of six sites were aspirated from the oral cavity with maximum (11) aspirates taken from alveolar ridge. The results of FNAC revealed that there were 32 malignant and 8 benign aspirates. Confirmation through histopathological analysis came for 31/32 malignant cases while one was falsely given positive for malignancy on FNAC. Among a total of 40 cases, 31(77%) cases diagnosed were found to be malignant and remaining 9(23%) were benign. The FNAC results revealed 32 malignant and 8 benign lesions. Histopathology of the subsequent surgically excised specimen showed malignant lesions in 31(77%) and benign in 9(23%) patients. As a whole, it was found that the absolute sensitivity for introral FNAC was 100% and specificity 89% with positive predictive value of 97% and negative predictive value of 100%. Conclusion: Cytological diagnosis was almost corroborative with final histopathological diagnosis in all cases, with very few exceptions, exhibiting high diagnostic accuracy.

• Asian Pacific Journal of Cancer Prevention
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• 제16권2호
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• pp.707-712
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• 2015

Background: To evaluate use of magnetic resonance imaging (MRI) and a logistic model including risk factors for lymph node metastasis for improved diagnosis. Materials and Methods: The subjects were 176 patients with rectal cancer who underwent preoperative MRI. The longest lymph node diameter was measured and a cut-off value for positive lymph node metastasis was established based on a receiver operating characteristic (ROC) curve. A logistic model was constructed based on MRI findings and risk factors for lymph node metastasis extracted from logistic-regression analysis. The diagnostic capabilities of MRI alone and those of the logistic model were compared using the area under the curve (AUC) of the ROC curve. Results: The cut-off value was a diameter of 5.47 mm. Diagnosis using MRI had an accuracy of 65.9%, sensitivity 73.5%, specificity 61.3%, positive predictive value (PPV) 62.9%, and negative predictive value (NPV) 72.2% [AUC: 0.6739 (95%CI: 0.6016-0.7388)]. Age (<59) (p=0.0163), pT (T3+T4) (p=0.0001), and BMI (<23.5) (p=0.0003) were extracted as independent risk factors for lymph node metastasis. Diagnosis using MRI with the logistic model had an accuracy of 75.0%, sensitivity 72.3%, specificity 77.4%, PPV 74.1%, and NPV 75.8% [AUC: 0.7853 (95%CI: 0.7098-0.8454)], showing a significantly improved diagnostic capacity using the logistic model (p=0.0002). Conclusions: A logistic model including risk factors for lymph node metastasis can improve the accuracy of MRI diagnosis of rectal cancer.

• Journal of Chest Surgery
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• 제33권8호
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• pp.669-675
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• 2000

Background: Tuberculous pleurisy is the leading cause of pleural effusion in Korea. And differential diagnosis of tuberculous pleurisy with other cause is clinically very important. Traditional diagnostic methods such as routine analysis of pleural fluid, staining for acid-fast bacilli or pleural biopsy have major inherent limitaion. This study was designed to evaluate the significance of pleural fluid polymerase chain reaction(PCR) and adenosine deaminase (ADA) activity in early diagnosis of tuberculous pleurisy. Material and Method: Between March 1996 and July 1997, 198 patients with pleural effusion reviewed retrospectively. The study group included 112 cases with tuberculous effusion and 86 cases with non-tuberculous effusions, whose diagnoses were confirmed by pleural biopsy, microbiological methods, or cytology. We compared the results of PCR and pleural fluid levels of ADA between tuberculous and non-tuberculous effusions. Result: Mean age was 47.54$\pm$19.52 years(range 2 to 85 years). The positive rate of PCR was significantly higher in tuberculous group than non-tuberculous group(p<0.05). The sensitivty, specificity, positive predictive value(PPV), and negative predictive value(NPV) for PCR were 31.7, 90.9, 83.0, and 48.8%, respectively. Mean ADA activity was significantly higher in tuberculous group than non-tuberculous group(83.2 U/L vs 49.8 U/L)(p<0.05). With diagnostic thresholds of 40 U/L, the sensitivity, specificity, PPV, and NPV of ADA for tuberculosis were 75.9, 70.9, 77.3, and 69.3% respectively. At a level of 70 U/L, the sensitivity, specificity, PPV, and NPV of ADA for tuberculosis were 70.1, 75.9, 82.9, and 60.3% respectively. Conclusion: PCR is very highly specific, but less sensitive methods in diagnosis of tuberculous pleurisy. But ADA level of pleural fluid has acceptable sensitivity and specificity in diagnosis of tuberculous pleurisy. ADA activity is more useful test in the evaluation of pleural effusions.

• Journal of Electrical Engineering and Technology
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• 제12권2호
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• pp.886-889
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• 2017

An active Fault Tolerant Model Predictive Control (FTMPC) using Fuzzy scheduler is developed. Fault tolerant Control (FTC) system stages are broadly classified into two namely Fault Detection and Isolation (FDI) and fault accommodation. Basically, the faults are identified by means of state estimation techniques. Then using the decision based approach it is isolated. This is usually performed using soft computing techniques. Fuzzy Decision Making (FDM) system classifies the faults. After identification and classification of the faults, the model is selected by using the information obtained from FDI. Then this model is fed into FTC in the form of MPC scheme by Takagi-Sugeno Fuzzy scheduler. The Fault tolerance is performed by switching the appropriate model for each identified faults. Thus by incorporating the fuzzy scheduled based FTC it becomes more efficient. The system will be thereafter able to detect the faults, isolate it and also able to accommodate the faults in the sensors and actuators of the Continuous Stirred Tank Reactor (CSTR) process while the conventional MPC does not have the ability to perform it.