• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.16 no.2
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• pp.46-56
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• 2003

Objects: The purpose of this thesis is to consider classification of Wibub(위법), heating method of Wibub(위법) and the diseases for which Wibub(위법) is efficacious through bibliographic basements. Methods: We bibliographically studied on Wibub(위법) through 20 existing oriental documents. Results: Summarized as follows; 1. Wibub(위법) is an external therapy of applying heated herbal powder or granules wrapped in a cloth or applying heated implements to the affected part. 2. Wibub(위법) is divided into two types. One is Yakwi(약위) which uses medicine, the other is Wibub(위법) which only uses implements. 3. The heating methods of Wibub(위법) are various. there are using directly heated medicine, using heated implement and using Naengwi(냉위) and Yeolwi(열위) in turns. 4. Wibub(위법) is efficacious for mammary disease like as acute mammaritis, mastitis, anal disease like as hemorrhoids, proctoptosis, sore, muscle disease, multiple abscess, pyogenic infection of bone, gonarthritis externally and efficacious for cold paralysis, cold limbs, vomiting with diarrhea, mass in abdomen, abdominal pain, constipation, urinary disease like as dysuria, ischuria internally. Conclusions: As the aboves. Wibub(위법) is able to be used variously in clinical cases. so we consider that it is necessary to study methods which improve practical use of Wibub(위법).

• Journal of Korea Multimedia Society
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• v.24 no.2
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• pp.233-244
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• 2021

Recently, several ICT-based cat studies have produced some successful results, according to academic and industry sources. However, research on the level of simply identifying the cat's condition, such as the behavior and sound classification of cats based on images and sound signals, has yet to be found. In this paper, based on the veterinary scientific knowledge of cats, a practical and academic cat monitoring and disease diagnosis system is proposed to monitor the health status of the cat 24 hours a day by automatically categorizing and analyzing the behavior of the cat with location information using LSTM with a beacon sensor and a raspberry pie that can be built at low cost. Validity of the proposed system is verified through experimentation with cats in actual custody (the accuracy of the cat behavior classification and location identification was 96.3% and 92.7% on average, respectively). Furthermore, a rule-based disease analysis system based on the veterinary knowledge was designed and implemented so that owners can check whether or not the cats have diseases at home (or can be used as an auxiliary tool for diagnosis by a pet veterinarian).

• Tuberculosis and Respiratory Diseases
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• v.39 no.5
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• pp.380-385
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• 1992

• The Plant Pathology Journal
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• v.15 no.2
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• pp.105-111
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• 1999

• Clinics in Shoulder and Elbow
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• v.21 no.2
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• pp.82-86
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• 2018

Background: Although a common shoulder disease, there are no accepted classification criteria for frozen shoulder (FS). This study therefore aimed to evaluate the accuracy of the conventionally used FS classification system. Methods: Primary FS patients (n=168) who visited our clinic from January 2010 to July 2015 were included in the study. After confirming restrictions of the glenohumeral joint motion and absence of history of systemic disease, trauma, shoulder surgery, shoulder muscle weakness, or specific x-ray abnormalities, the Zuckerman and Rokito's classification was employed for diagnosing primary FS. Following clinical diagnosis, each patient underwent a shoulder magnetic resonance imaging (MRI) and blood tests (lipid profile, glucose, hemoglobin A1c, and thyroid function). Based on the results of the blood tests and MRIs, the patients were reclassified, using the criteria proposed by Zuckerman and Rokito. Results: New diagnoses were ascertained including blood test results (16 patients with diabetes, 43 with thyroid abnormalities, and 149 with dyslipidemia), and MRI revealed intra-articular lesions in 81 patients (48.2%). After re-categorization based on the above findings, only 5 patients (3.0%) were classified having primary FS. The remaining 163 patients (97.0%) had either undiagnosed systemic or intrinsic abnormalities (89 patients), whereas 74 patients had both. Conclusions: These findings demonstrate that most patients clinically diagnosed with primary FS had undiagnosed systemic abnormalities and/or intra-articular pathologies. Therefore, a modification of the Zuckerman and Rokito's classification system for FS may be required to include the frequent combinations, rather than having a separate representation of systemic abnormalities and intrinsic causes.

• Progress in Superconductivity
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• v.7 no.1
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• pp.41-45
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• 2005

The diagnostic management of patients with chest pain remains a clinical challenge. Magnetocardiography (MCG) has been proposed as a new non-invasive method for detection of myocardial ischemia. To date, however, MCG technique is not intensively introduced for clinical use. One of the main reasons might be the absence of statistically valid and diagnostically clean criteria, which can determine the presence of certain heart disease. In this work, we suggested a new method to classify the diagnostic value of MCG for the detection of coronary artery disease (CAD) in patients with chest pain. MCG was recorded for three groups (healthy subjects and patients without and with CAD) by means of the 64 channel SQUID gradiometer system installed at a hospital. Using four parameters, which were found to be significantly different between groups, we evaluated a probability, in which parameters can be classified into each group based on the distribution function of the parameter in each group. For all parameters, sum of probabilities was compared between groups to determine the presence of CAD. Our classification method shows that the MCG can be a useful tool to predict the presence of CAD with sensitivity and specificity of higher than $80\%$ each.

• Journal of Cancer Prevention
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• v.23 no.4
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• pp.183-190
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• 2018

Background: As the number of big-cohort studies increases, validation becomes increasingly more important. We aimed to validate administrative database categorized as colorectal cancer (CRC) by the International Classification of Disease (ICD) 10th code. Methods: Big-cohort was collected from Clinical Data Warehouse using ICD 10th codes from May 1, 2003 to November 30, 2016 at Seoul National University Bundang Hospital. The patients in the study group had been diagnosed with cancer and were recorded in the ICD 10th code of CRC by the National Health Insurance Service. Subjects with codes of inflammatory bowel disease or tuberculosis colitis were selected for the control group. For the accuracy of registered CRC codes (C18-21), the chart, imaging results, and pathologic findings were examined by two reviewers. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for CRC were calculated. Results: A total of 6,780 subjects with CRC and 1,899 control subjects were enrolled. Of these patients, 22 subjects did not have evidence of CRC by colonoscopy, computed tomography, magnetic resonance imaging, or positron emission tomography. The sensitivity and specificity of hospitalization data for identifying CRC were 100.00% and 98.86%, respectively. PPV and NPV were 99.68% and 100.00%, respectively. Conclusions: The big-cohort database using the ICD 10th code for CRC appears to be accurate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.2924-2944
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• 2023

Alzheimer's disease (AD) is a neurological condition that is recognized as one of the primary causes of memory loss. AD currently has no cure. Therefore, the need to develop an efficient model with high precision for timely detection of the disease is very essential. When AD is detected early, treatment would be most likely successful. The most often utilized indicators for AD identification are the Mini-mental state examination (MMSE), and the clinical dementia. However, the use of these indicators as ground truth marking could be imprecise for AD detection. Researchers have proposed several computer-aided frameworks and lately, the supervised model is mostly used. In this study, we propose a novel 3D Convolutional Neural Network Multilayer Perceptron (3D CNN-MLP) based model for AD classification. The model uses Attention Mechanism to automatically extract relevant features from Magnetic Resonance Images (MRI) to generate probability maps which serves as input for the MLP classifier. Three MRI scan categories were considered, thus AD dementia patients, Mild Cognitive Impairment patients (MCI), and Normal Control (NC) or healthy patients. The performance of the model is assessed by comparing basic CNN, VGG16, DenseNet models, and other state of the art works. The models were adjusted to fit the 3D images before the comparison was done. Our model exhibited excellent classification performance, with an accuracy of 91.27% for AD and NC, 80.85% for MCI and NC, and 87.34% for AD and MCI.

• Journal of Physiology & Pathology in Korean Medicine
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• v.18 no.6
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• pp.1543-1547
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• 2004

In this study, symptoms, pathologies, compositions and clinical applications of 52 prescriptions for woman-related disease treatment descripted in Bang Yahk Hap Peun were investigated. The results were same as following; Classification of prescriptions for woman-related disease treatments was 23 prescriptions in high-chepter, prescriptions in 16 medium-chepter, and prescriptions in 13 low-chepter prescriptions and the frequency of clinical applications for high-chepter, medium-chepter and low-chepter prescriptions was 44%, 31% and 25%, respectively. Clinical applications of woman-related disease prescriptions were identified aocording to pre-pregnancy and post-birth, uterus, breast disease, before pregnancy. Infertile, emmeniopathy, uterus Blooding made practical application to high frequency in the treatments. Oriental Medical Pathology applied with prescriptions were Biheo(脾虛), Ganbinoyool(肝脾怒鬱), Infirmity(虛弱), 熱入血室, Jungpung(中風), Gihyulguheo(氣血俱虛), hyulheo(血虛), Aeohyul(瘀血) etc. Prescriptions applied with the most frequency in woman-related disease were Samuoltang(四物湯), Sagunjatang(四君子湯), Gungkuitang(芎歸湯), Boanbaekchuolsan(保安白朮散), Dangguibohyeltang(當歸補血湯), Sanhyointang(酸棗仁湯), Dohongsamuoltang(桃紅四物湯), Jipeisan(芷貝散), Silsosan(失笑散).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.1
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• pp.76-82
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• 2002

In this paper, we implemented on the classifier for differential diagnosis of laryngeals disease which is normal, polyp, nodule, palsy, and each step of glottic cancer using hierarchical neural network. We conducted on classifier of various vowels as /a/, /e/, /i/, /o/, /u/ from normal group, laryngeal disease group, each step of cancer group. The experimental result on classification of each vowels as follows. A /a/ vowel shows excellent classification result to the other vowels in regard to each Input parameters. Thus we implemented the hierarchical neural network for differential diagnosis of laryngeals disease using only /a/ vowel. A implemented hierarchical neural network is composed of each other laryngeals disease apply to each other parameter in each hierarchical layer. We take the voice signals from patient who get the laryngeal disease and glottic cancer, and then use the APQ, PPQ, vAm, Jitter, Shimmer, RAP as input parameter of neural networks.