• Journal of Yeungnam Medical Science
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• v.1 no.1
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• pp.13-23
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• 1984

Acute renal failure refers to a rapid reduction in renal function that usually occurs in an individual with no known previous renal disease. Development of a complication of acue renal failure in critically ill surgical patients is not unusual, and it causes high morbidity and mortality. Acute renal failure can be divided as Pre-renal (functional), Renal (organic), and Post-renal (obstructive) azotemia according to their etiologies. Early recognition and proper correction of pre-renal conditions are utter most important to prevent an organic damage of kidney. These measures include correction of dehydration, treatment of sepsis, and institution of shock therapy. Prolonged exposure to ischemia or nephrotoxin may lead a kidney to permanent parenchymal damage. A differential diagnosis between functional and organic acute renal failure may not be simple in many clinical settings. Renal functional parameters, such as $FENa^+$ or renal failure index, are may be of help in these situations for the differential diagnosis. Provocative test utilyzing mannitol, loop diuretics and renovascular dilators after restoration of renal circulation will give further benefits for diagnosis or for prevention of functional failure from leading to organic renal failure. Converting enzyme blocker, dopamine, calcium channel blocker, and propranolol are also reported to have some degree of renal protection from bioenergetic renal insults. Once diagnosis of acute tubular necrosis has been made, all measures should be utilized to maintain the patient until renal tubular regeneration occurs. Careful regulation of fluid, electrolyte, and acid-base balance is primary goal. Hyperkalemia over 6.5 mEq/l is a medical emergency and it should be corrected immediately. Various dosing schedules for medicines excreting through kidney have been suggested but none was proved safe and accurate. Therefore blood level of specific medicines better be checked before each dose, especially digoxin and Aminoglycosides. Indication for application of ultrafiltration hemofilter or dialysis may be made by individual base.

• Journal of Gastric Cancer
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• v.19 no.3
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• pp.315-328
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• 2019

Purpose: To investigate the clinical value of serum miR-221-3p and miR-122-5p expression levels in the diagnosis and prognosis of gastric cancer. Materials and Methods: Serum samples from 141 gastric cancer cases (gastric cancer group), 110 gastric polyps (gastric polyp group), and 75 healthy people (healthy control) were used to detect miR-221-3p and miR-122-5p expression using real-time reverse transcription polymerase chain reaction. Results: Serum miR-221-3p expression was significantly higher in the gastric cancer group than in the gastric polyp group, and it was significantly lower than that before operation. The miR-221-3p expression was significantly higher in the death group than in the survival group. The proliferation and migration ability significantly increased and the apoptosis rate significantly decreased by miR-221-3p transfection in gastric cancer cells. In contrast, the function of miR-122-5p in gastric cancer cells was opposite of miR-221-3p. Serum miR-221-3p expression was negatively correlated with that of miR-122-5p in gastric cancer. Serum miR-221-3p and miR-122-5p expressions were significantly correlated with the degree of differentiation, tumor, node, metastasis stage, lymph node metastasis, and invasion depth. miR-221-3p and miR-122-5p expression levels were independent prognostic factors for postoperative gastric cancer. In the diagnosis and predicting prognosis of gastric cancer, receiver operating characteristic analysis revealed that the area under curve of combined detection of serum miR-221-3p and miR-122-5p expression had a greater diagnostic effect than either single maker. Conclusions: The miR-221-3p and miR-122-5p are involved in the development of gastric cancer, and they have important clinical values in gastric cancer diagnosis and prognosis.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.77-87
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• 2023

Wind turbines playing a critical role in renewable energy generation, accurately assessing their operational status is crucial for maximizing energy production and minimizing downtime. This study conducts a comparative analysis of different neural network models for wind turbine condition diagnosis, evaluating their effectiveness using a dataset containing sensor measurements and historical turbine data. The study utilized supervisory control and data acquisition data, collected from 2 MW doubly-fed induction generator-based wind turbine system (Model HQ2000), for the analysis. Various neural network models such as artificial neural network, long short-term memory, and recurrent neural network were built, considering factors like activation function and hidden layers. Symmetric mean absolute percentage error were used to evaluate the performance of the models. Based on the evaluation, conclusions were drawn regarding the relative effectiveness of the neural network models for wind turbine condition diagnosis. The research results guide model selection for wind turbine condition diagnosis, contributing to improved reliability and efficiency through advanced neural network-based techniques and identifying future research directions for further advancements.

• Journal of Physiology & Pathology in Korean Medicine
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• v.18 no.6
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• pp.1938-1944
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• 2004

In this study, when we make a diagnosis of constitution using QSCC Ⅱ(Questionnaire of Sasang Constitution Classification). data mining techniques are applied to seek the classification function for improving the accuracy. Data used in the analysis are the questionnaires of 1051 patients who had been treated in Dong Eui Oriental Medical Hospital and Kyung Hee Oriental Medical Hospital. The criteria for data cleansing are the response pattern in the opposite questionnaires and the positive proportion of specific questionnaires in each constitution. And the criteria for variable selection are the test of homogeneity in frequency analysis and the coefficients in the linear discriminant function. Discriminant analysis model and decision tree model are applied to seek the classification function into Sasang constitution. The accuracy in learning sample is similar in two models, the higher accuracy in test sample is obtained in discriminant analysis model.

• Journal of Korea Multimedia Society
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• v.23 no.5
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• pp.625-632
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• 2020

In the diagnosis of lung cancer, the tumor size is measured by the longest diameter of the tumor in the entire slice of the CT. In order to accurately estimate the size of the tumor, it is better to measure the volume, but there are some limitations in calculating the volume in the clinic. In this study, we propose an algorithm to segment lung cancer by applying a custom loss function that combines focal loss and dice loss to a U-Net model that shows high performance in segmentation problems in chest CT images. The combination of values of the various parameters in custom loss function was compared to the results of the model learned. The purposed loss function showed F1 score of 88.77%, precision of 87.31%, recall of 90.30% and average precision of 0.827 at α=0.25, γ=4, β=0.7. The performance of the proposed custom loss function showed good performance in lung cancer segmentation.

• Journal of Physiology & Pathology in Korean Medicine
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• v.25 no.2
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• pp.318-321
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• 2011

In this study, when a physician make a diagnosis of the Pattern Identifications(PIs) of stroke patients, the development methods of the PIs classification function is considered by diagnostic questionnaire of the PIs for stroke patients. Clinical data collected from 1,502 stroke patients who was identically diagnosed for the PIs subtypes diagnosed by two clinical experts with more than 3 years experiences in 13 oriental medical hospitals. In order to develop the classification function into PIs using the 44 items-Fire&heat(19), Qi-deficiency(11), Yin-deficiency(7), Dampness phlegm(7)- of them was significant statistically by univariate analysis in 61 questionnaires totally, we make some comparisons of the results of discriminant analysis model and generalized logit model. The overall diagnostic accuracy rate of the PIs subtypes for discriminant model(74.37%) was higher than 3% of generalized logit model(70.09%).

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.279-282
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• 1996

The authors have already proposed a method for grouping of inputs of a logical circuit under test (LCUT) by use of M-sequence correlation. We call this method as input grouping (IG) method. In this paper, the authors propose a new method to estimate the faulty part in the circuit by use of IG when some information on the candidate of faulty part can be obtained beforehand. The relationship between IG and fault probabilities of a LCUT, and undetected fault ratios are investigated for various cases. Especially the investigation was made in case where the IG was calculated by use of n correlation functions (I $G_{inp}$). From the theoretical study and simulation results it is shown that the estimation error ratio of fault probabilities and undetected fault ratio of LCUT are sufficiently small even when only a part of correlation functions are used. It is shown that the number of correlation functions which are to be memorized to calculate IG can be considerably reducible from 2$^{n}$ - 1 to n by use of I $G_{inp}$. So this method would be very useful for a fault diagnosis of actual logic circuit.uit.

• IE interfaces
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• v.21 no.4
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• pp.394-402
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• 2008

The objective of this paper is to design segmentation algorithm for applying the breast ultrasound image to CAD(Computer Aided Diagnosis). This study is conducted after understanding limits, used algorithm and demands of CAD system by interviewing with a medical doctor and analyzing related works based on a general CAD framework that is consisted of five step-establishment of plan, analysis of needs, design, implementation and test & maintenance. Detection function of CAD is accomplished by Canny algorithm and arithmetic operations for segmentation. In addition to, long computing time is solved by extracting ROI (Region Of Interests) and applying segmentation technical methods based morphology algorithm. Overall course of study is conducted by verification of medical doctor. And validity and verification are satisfied by medical doctor's confirmation. Moreover, manual segmentation of related works, restrictions on the number of tumor and dependency of image resolution etc. was solved. This study is utilized as a support system aided doctors' subjective diagnosis even though a lot of future studies is needed for entire application of CAD system.

• The Korean Journal of Nuclear Medicine
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• v.38 no.3
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• pp.209-217
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• 2004

Evaluation of dementia in patients with early symptoms of cognitive decline is clinically challenging, but the need for early, accurate diagnosis has become more crucial, since several medication for the treatment of mild to moderate Alzheimer' disease are available. Many neurodegenerative diseases produce significant brain function alteration even when structural imaging (CT or MRI) reveal no specific abnormalities. The role of PET and SPECT brain imaging in the initial assessment and differential diagnosis of dementia is beginning to evolve vapidly and growing evidence indicates that appropriate incorporation of PET into the clinical work up can improve diagnostic and prognostic accuracy with respect to Alzheimer's disease, the most common cause of dementia in the geriatric population. in the fast few years, studios comparing neuropathologic examination with PET have established reliable and consistent accuracy for diagnostic evaluations using PET - accuracies substantially exceeding those of comparable studies of diagnostic value of SPECT or of both modalities assessed side by side, or of clinical evaluations done without nuclear imaging. This review deals the role of functional brain imaging techniques in the evaluation of dementias and the role of nuclear neuroimaging in the early detection and diagnosis of Alzheimer's disease.

• Journal of Oral Medicine and Pain
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• v.24 no.2
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• pp.137-143
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• 1999

Aucubin, the natural product, which is isolated from Aucuba japonica, has a variety of pharmacological effects such as liver-protective function, inhibition of liver RNA and protein biosynthesis, hypotensive activity and antimicrobial effect, etc. This study was performed to investigate the effects of iridoid compounds on wound healing. The author prepared 0.1% aucubin solution and 0.1% aucubin ointment as an active form, aucubigenin to which aucubin was converted by ${\beta}$-glucosidase. Artificial surgical wound was made on either 1cm lateral side of the dorsal midline along the axis of spine of Sprague-Dawley rats under sterile technique. Application of 0.1% aucubin solution or 0.1% aucubin ointment to surgical wound was done daily. Light microscopic examination was performed on the postsurgical 3 days, 5 days, and 9 days. The 0.1% aucubin solution group epithelialized earlier than the control group and the fibrosis of granulation tissue of both aucubin groups were more prominent than the control group. Collectively, this study suggests the possibility of aucubin as a topical agent. Further research should be performed on the mechanism of aucubin on wound healing and proper formulation for effective topical agents.