• Parasites, Hosts and Diseases
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• v.59 no.4
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• pp.363-368
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• 2021

Despite the synergistic effect of Opisthorchis viverrini and Helicobacter pylori co-infection on pathogenesis of severe hepatobiliary abnormalities (HBA) including advanced periductal fibrosis and replace with cholangiocarcinoma (CCA) have been established, the immune response to H. pylori in O. viverrini infected population has never been explored. Hence, this study aimed to investigate the antibody responses to 2 immunogenic H. pylori proteins in O. viverrini-infected patients with HBA and CCA. The risk analysis by multinomial logistic regression revealed that GroEL seropositivity was associated with higher risks of hepatobiliary abnormalities and CCA with adjusted odds ratios (95% confidence intervals) of 2.11 (95% CI=1.20-3.71, P=0.008) and 2.13 (95% CI=1.21-3.75, P=0.009), respectively. These findings indicate that GroEL seropositivity might be a biomarker for early detection of O. viverrini associated HBA and CCA.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.116-118
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• 1997

In hippocampal morphology Abnormalities, including unilateral or bilateral volume loss, are known to occur in epilepsy, Alzheimer's disease, and in certain amnestic syndromes. To detect such abnormalities in hippocampal morphology, we present a method that combines region growing and dynamic contour model to detect hippocampus from MRI brain data. The segmentation process is performed two steps. First region growing with a seed point is performed in the region of hippocampus and the initial contour of dynamic contour model is obtained. Second, the initial contour is modified on the basis of criteria that integrate energy with contour smoothness and the image gradient along the contour. As a result, this method improves fairly sensitivity to the choice of the initial seed point, which is often seen by conventional contour model. The power and practicality of this method have been tested on two brain datasets. Thus, we have developed an effective algorithm to extract hippocampus from MRI brain data.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.8
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• pp.3825-3827
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• 2012

FISH is one of the most sensitive molecular methods to detect genetic abnormalities with DNA probes. When cytogenetic studies are normal or insufficient, FISH may detect cryptic rearrangements, rare or slowly proliferative abnormal populations in non-mitotic cells. We cytogenetically evaluated 70 childhood ALL - 67.1% were found to have an abnormal karyotype. The 23 patients (32.9%) with a normal karyotype were analyzed by FISH applying two probes; TEL/AML1 and MYB which detect cryptic rearrangements of t(12;21)(p13;q22) and deletion of (6q) respectively, associated with a good prognosis. Out of 23 patients, one was positive for t(12;21)(p13;q22) (4.3%). None of our patients were positive for MYB del(6q). Two patients showed an extra signal for MYB on chromosomes other than 6 (8.6 %) indicating amplification or duplication. Findings were compared with the available literature. Our study clearly indicated the integrated FISH screening method to increase the abnormality detection rate in a narrow range. FISH is less useful for diagnostic study of patients with suspected del(6q) but it helps in detecting known cryptic rearrangements as well as identification of new abnormalities(translocation , duplication and amplification) at the gene level.

• Tuberculosis and Respiratory Diseases
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• v.70 no.1
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• pp.10-20
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• 2011

Various diseases can diffusely involve central airways, including the trachea and main stem bronchi. Central airway abnormalities are frequently not apparent or are overlooked on chest radiographs, even though the patient may have significant symptoms. Recent advances in spiral and multi-detector computed tomography (CT) with multi-planar reconstruction and three-dimensional demonstration, including virtual bronchoscopy, allow for excellent display of central airway anatomy and abnormalities with visualization of accurate locations of lesions. Early detection and proper diagnosis of airway diseases based on various radiographic findings will help determine appropriate treatment, including surgical planning and evaluation of treatment response. Herein we describe and illustrate the imaging findings of a wide spectra of diffuse central airway diseases.

• The Korean Journal of Pain
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• v.26 no.2
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• pp.181-185
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• 2013

Infective spondylodiscitis is a rare complication that can occur after interventional spinal procedures, of which symptoms are usually back pain and fever. Early diagnosis of infective spondylodiscitis is critical to start antibiotics and to improve prognosis. Laboratory examinations including complet blood cell count (CBC), erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) are conventional tools for the early detection of infectious spondylitis. However, we experienced infective spondylodiscitis after cervical nucleoplasty which did not display any laboratory abnormalities, but was diagnosed through an MRI. A patient with cervical disc herniation received nucleoplasty at C5/6 and C6/7. One month later, the patient complained of aggravated pain. There were neither signs of chill nor fever, and the laboratory results appeared normal. However, the MRI findings were compatible with infectious spondylodiscitis at the nucleoplasty site. In conclusion, infectious spondylodiscitis can develop after cervical nucleoplasty without any laboratory abnormalities. Therefore, an MRI should be taken when there is a clinical suspicion for infection in order to not miss complications after interventional procedures, even if the laboratory findings are normal.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.97-100
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• 2004

The identification of the DNA structure as a double-stranded helix consting of two nucleotide chain molecules was a milestone in modern molecular biology. The DNA chip technology is based on reverse hybridization that follows the principle of complementary binding of double-stranded DNA. DNA chip can be described as the deposition of defined nucleic acid sequences, probes, on a solid substrate to form a regular array of elements that are available for hybridization to complementary nucleic acids, targets. DNA chips based on cDNA clons, oligonucleotides and genomic clons have been developed for gene expression studies, genetic variation analysis and genomic changes associated with disease including cancers and genetic diseases. DNA chips for gene expression profiling can be used for functional analysis in human eel Is and animal models, disease-related gene studies, assessment of gene therapy, assessment of genetically modified food, and research for drug discovery. DNA chips for genetic variation detection can be used for the detection of mutations or chromosomal abnormalities in cnacers, drug resistances in cancer cells or pathogenic microbes, histocompatibility analysis for transplantation, individual identification for forensic medicine, and detection and discrimination of pathogenic microbes. The DNA chip will be generalized as a useful tool in clinical diagnostics in near future. Lab-on-a chip and informatics will facilitate the development of a variety of DNA chips for diagnostic purpose.

• The Korean Journal of Nuclear Medicine
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• v.36 no.1
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• pp.34-38
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• 2002

Positron emission tomography(PET) is an imaging method that employs radionuclide and tomography techniques. Since 1995, we applied PET not only to the diagnosis of breast cancer but also to the detection of abnormalities in the augmented breast and to the detection of metastasis. Until 2001, we evaluated 242 breast cases by PET at PET center of Seoul National University Hospital. Our group has reported serially at the international journals. In the first report, PET showed high sensitivity for detecting breast cancer, both the primary and axillary node metastasis. A total of 27 patients underwent breast operations based on PET results at Seoul National University Hospital from 1995 to 1996. The diagnostic accuracy of PET were 97% for the primary tumor mass and 96% for axillary lymph node metastasis. In case of the breast augmented, PET also showed excellent diagnostic results for primary breast cancer and axillary lymph node metastasis where mammography and ultrasound could not diagnose properly. PET also had outstanding results in the detection of recurrent or metastatic breast cancer(sensitivity 94%, specificity 80%, accuracy 89%). In addition, our study gave some evidence that PET could be applied further to evaluate the growth rate of tumors by measuring SUV, and finally to prognosticated the disease. PET could also be applied to evaluate the response after chemotherapy to measure its metabolic rate and size. In conclsion, PET is a highly sensitive, accurate diagnostic tool for breast cancer of primary lesion in various conditions including metastasis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.78-81
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• 2021

Through the smart factory construction project, sensors can be installed in manufacturing production facilities and various process data can be collected in real time. Through this, research on real-time facility anomaly detection is being actively conducted to reduce production interruption due to facility abnormality in the manufacturing process. In this paper, to detect abnormalities in production facilities, the manufacturing data was applied to deep learning models Autoencoder(AE), VAE(Variational Autoencoder), and AAE(Adversarial Autoencoder) to derive the results. Manufacturing data was used as input data through a simple moving average technique and preprocessing process, and performance analysis was conducted according to the window size of the simple movement average technique and the feature vector size of the AE model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.216-223
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• 2019

Fault detection during production processes is one of the required operational tasks to run production processes both safely and consistently. Unexpected operational events or undetected process faults can have a serious impact on the production systems and subsequently on the final products' quality. In addition, such situations may lead to malfunctions or breakdowns of production processes. To reliably detect such abnormalities, a new one-class classification-based detection scheme has recently been developed The proposed method consists of four steps:1) noise filtering, 2) feature selection, 3) nonlinear representation and 4) outlier detection. The performance of the proposed scheme was demonstrated using the multivariate data obtained from a simulation process. The results have shown that the proposed method produced reliable monitoring results and outperforms any existing methods with an average improvement of 25.4%. The use of proper feature selection in the proposed framework yielded better detection performance.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.401-410
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• 2021

Recently, as cyber attacks targeting industrial control systems increase, various studies are being conducted on the detection of abnormalities in industrial processes. Considering that the industrial process is deterministic and regular, It is appropriate to determine abnormality by comparing the predicted value of the detection model from which normal data is trained and the actual value. In this paper, HAI Datasets 20.07 and 21.03 are used. In addition, an ensemble model is created by combining models that have applied different time steps to Gated Recurrent Units. Then, the detection performance of the single model and the ensemble recurrent neural networks model were compared through various performance evaluation analysis, and It was confirmed that the proposed model is more suitable for abnormal detection in industrial control systems.