• Journal of Chest Surgery
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• v.33 no.8
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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.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.15
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• pp.6253-6255
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• 2014

Background: Colorectal cancer (CRC) is considered to be a main cause of malignancy-related death in the world, being commonly diagnosed in both men and women. It is the third leading cause of cancer dependent death in the world and there are one million new cases diagnosed per year. In Iran the incidence of colorectal cancer has increased during the last 25 years and it is the fifth cause of cancer in men and the third in women. Materials and Methods: In this article we analyzed the survival of 475 colorectal patients of Taleghani hospital in Tehran with the semi-parametric competing-risks model. Results: There were 55% male cases and at the time of the diagnosis most of the patients were between 48 and 67years old. The probability of a patient death from colorectal cancer with survival of more than 25 years was about 0.4. Body mass index, height, tumour site and gender had no influence. Conclusions: According to these data and by using semi-parametric competing-risks method, we found out that only age at diagnosis has a significant effect on these patient survival time.

• Computers and Concrete
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• v.2 no.6
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• pp.439-454
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• 2005

When deterioration of concrete is observed in a structure, it is highly desirable to determine the cause of such deterioration. Only by understanding the cause can an appropriate repair strategy be implemented to address both the cause and the symptom. In colder climates, bridge deck deterioration is often caused by chlorides from de-icing salts, which penetrate the concrete and depassivate the embedded reinforcement, causing corrosion. Bridge decks can also suffer from other deterioration mechanisms, such as alkali-silica reaction, freeze-thaw, and shrinkage. There is a need for a comprehensive and integrative system to help with the inspection and evaluation of concrete bridge deck deterioration before decisions are made on the best way to repair it. The purpose of this research was to develop a model to help with the diagnosis of concrete bridge deck deterioration that integrates the symptoms observed during an inspection, various deterioration mechanisms, and the probability of their occurrence given the available data. The model displays the diagnosis result as the probability that one of four deterioration mechanisms, namely shrinkage, corrosion of reinforcement, freeze-thaw and alkali-silica reaction, is at fault. Sensitivity analysis was performed to determine which probabilities in the model require refinement. Two case studies are included in this investigation.

• Journal of Yeungnam Medical Science
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• v.39 no.2
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• pp.81-88
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• 2022

Vertigo is the sensation of self-motion of the head or body when no self-motion is occurring or the sensation of distorted self-motion during an otherwise normal head movement. Representative peripheral vertigo disorders include benign paroxysmal positional vertigo, Ménière disease, and vestibular neuritis. Vestibular neuritis, also known as vestibular neuronitis, is the third most common peripheral vestibular disorder after benign paroxysmal positional vertigo and Ménière disease. The cause of vestibular neuritis remains unclear. However, a viral infection of the vestibular nerve or ischemia of the anterior vestibular artery is known to cause vestibular neuritis. In addition, recent studies on immune-mediated mechanisms as the cause of vestibular neuritis have been reported. The characteristic clinical features of vestibular neuritis are abrupt true-whirling vertigo lasting for more than 24 hours, and no presence of cochlear symptoms and other neurological symptoms and signs. To accurately diagnose vestibular neuritis, various diagnostic tests such as the head impulse test, bithermal caloric test, and vestibular-evoked myogenic potential test are conducted. Various treatments for vestibular neuritis have been reported, which are largely divided into symptomatic therapy, specific drug therapy, and vestibular rehabilitation therapy. Symptomatic therapies include generalized supportive care and administration of vestibular suppressants and antiemetics. Specific drug therapies include steroid therapy, antiviral therapy, and vasodilator therapy. Vestibular rehabilitation therapies include generalized vestibular and customized vestibular exercises.

• Proceedings of the Korean Nuclear Society Conference
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• 2004.05a
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• pp.218-218
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• 2004

• Journal of Korean Medical classics
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• v.22 no.1
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• pp.71-85
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• 2009

For having good therapeutic value, putting the ideal of diagnosis and treatment based on overall analysis of symptoms and signs[辨證施治] into practice is very important, so the Eastern Medicine's peculiar diagnosis without interference by the western medical diagnosis is very important. The peculiar method of Eastern Medicine's diagnosis is four methods of diagnosis(四診法), a joint term for inspection, auscultation and olfaction, interrogation, pulse feeling and palpation. In the process of interrogation[問診], from analyzing the perspiration phase, doctor can get various physical information. Especially perspiration from particular region can be a clue for founding focus or cause of disease. This thesis divide the phase of perspiration into eight bodily region, perspiration from all body, head, face, back, chest and armpit, stomach, pubic region and lower part, hands and feet, and inquire the possible causes and principles of these perspirations. In conclusion, the regional perspiration can be a clue point out the origin of fever and condition of Gi(氣) flow. Perspiration from head, back, chest and armpit, hands and feet means that certain fever cannot extend to the outside of body, and at the same time, means the Gi(氣) flow of outside is being intercepted. So the perspirations from that region become an object of medical treatment.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.4
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• pp.280-284
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• 2016

Stability and reliability of a power system in many respects depend on the condition of power transformers. Essential devices as power transformers are in a transmission and distribution system. Being one of the most expensive and important elements, a power transformer is a highly essential element, whose failures and damage may cause the outage of a power system. To detect the power transformer faults, dissolved gas analysis (DGA) is a widely-used method because of its high sensitivity to small amount of electrical faults. Among the various diagnosis methods, Rogers diagonsis method has been widely used in transformer in service. But this method cannot offer accurate diagnosis for all the faults. This paper proposes a fault diagnosis method of oil-filled power transformers using PNN(Probability Neural Network) based Rogers diagnosis method. The test result show better performance than conventional Rogers diagnosis method.

• Nuclear Engineering and Technology
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• v.32 no.3
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• pp.261-273
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• 2000

During an extensive review made as part of the Integrated Diagnosis System project of the Maiden Reactor Project, MOAS (Maryland Operator Advisory System) was identified as one of the most thorough systems developed thus far. MOAS is an integrated on-line diagnosis system that encompasses diverse functional aspects that are required for an effective process disturbance management: (1) intelligent process monitoring and alarming, (2) on-line sensor data validation and sensor failure diagnosis, (3) on-line hardware (besides sensors) failure diagnosis, and (4) real-time corrective measure synthesis. The MOAS methodology was used at the Maiden Man-Machine Laboratory HAMMLAB of the OECD Maiden Reactor Project. The performance of MOAS, developed in G2 real-time expert system shell for the high-pressure preheaters of the NORS process in the HAMMLAB, was tested against a variety of transient scenarios, including failures of the control valves and sensors, and tube leakage of the preheaters. These tests showed that MOAS successfully carried out its intended functions, i.e., quickly recognizing an occurring disturbance, correctly diagnosing its cause, and presenting advice on its control to the operator. The lessons learned and insights gained during the implementation and performance tests also are discussed.

• Radiation Oncology Journal
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• v.7 no.2
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• pp.259-267
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• 1989

Forty one patients with para-aortic node metastases from carcinoma of the uterine cervix treated with radiotherapy at Department of Radiation Oncology, Yonsei University, College of Medicine from January 1982 to December 1987 were retrospectively analyzed. Eleven patients were diagnosed at the time of diagnosis of carcinoma of the cervix (early diagnosis) and 30 patients were diagnosed during follow up period after definitive radiotherapy of primary site (late diagnosis). The most important factors affecting the survival in this study were time of diagnosis and dose of irradiation. Overall 5 year actuarial survival rate of 41 patients was $25.7\%$. Five year survival rate for early diagnosis was $60.3\%$, but late diagnosis was $16.9\%$. And survival rate for high dose (over 4000 cGy) radiation group and low dose radiation group were $42.2\%\;and\;8.9\%$ respectively The most leading cause of death was para-aortic node failure, so early diagnosis and maximum palliation with full dose radiotherapy (over 4000 cGy) is necessary to improve the survival and the quality of life.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.89-99
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• 2018

Downtime and malfunction of industrial rotor machines represents a crucial cost burden and productivity loss. Fault diagnosis of this equipment has recently been carried out to detect their fault(s) and cause(s) by using fault classification methods. However, these methods are of limited use in detecting rotor faults because of their hypersensitivity to unexpected and different equipment conditions individually. These limitations tend to affect the accuracy of fault classification since fault-related features calculated from vibration signal are moved to other regions or changed. To improve the limited diagnosis accuracy of existing methods, we propose a new approach for fault diagnosis of rotor machines based on the model generated by supervised learning. Our work is based on feature residual values from vibration signals as fault indices. Our diagnostic model is a robust and flexible process that, once learned from historical data only one time, allows it to apply to different target systems without optimization of algorithms. The performance of the proposed method was evaluated by comparing its results with conventional methods for fault diagnosis of rotor machines. The experimental results show that the proposed method can be used to achieve better fault diagnosis, even when applied to systems with different normal-state signals, scales, and structures, without tuning or the use of a complementary algorithm. The effectiveness of the method was assessed by simulation using various rotor machine models.