• Journal of Digital Convergence
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• v.11 no.9
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• pp.229-238
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• 2013

Out-of-hospital cardiac arrest is a major public health problem in Korea. The survival rate to discharge remains at approximately 3.5% and only 1% have good neurological function. To increase the survival rate, prehospital care should restore spontaneous circulation. The purpose of this study was to analyze the factors associated with return of spontaneous circulation(ROSC) after out-of-hospital cardiac arrest. Data used for this study were collected from KCDC Out-of-Hospital Cardiac Arrest Surveillance 2009. As for the results of decision tree analysis, it is clear that prehospital CPR, cardiac arrest witness, activity, past history(cancer/heart disease/stroke), place, bystander CPR, response time, age, etc are significant contributing factors in ROSC. Among 16 cardiac arrest types from decision tree classification, the ROSC rate of type 1 is the highest(29.6%). Also notable is the fact that bystander CPR was strongly correlated with ROSC of patents with cardiac arrest occurring in non-public places. Community resources should be concentrated on increasing bystander CPR and early prehospital emergency care.

• Journal of Haehwa Medicine
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• v.10 no.1
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• pp.269-286
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• 2001

Objectives : This Investigation was aimed to find out the Classification of Cause and the Effect of Acupuncture and Moxibustion Treatment for Dentalgia Methods : We surveyed the oriental medical books from $\ll$HungTiNeiChing$\gg$ to recent published books concerning the Acupuncture therapy for Dentalgia Results : 1. Since the time of $\ll$HungTiNeiChing$\gg$ there was called "yateng", "yatong", "chiyaqutong", "kouchitong", "nichi", "chichong", "fengchi", "chongshitong", "chongshiyachi", "chifengzhongtong", "chiyinzhong", "yachuangzhongtong" 2. The Oriental Medical cause of Dentalgia are fire, wind, cold, blood stasis, stomach-heat, phlegm, difficiency of kidney, late snack, insect and wound, and then the Western Medical cause are cacodontia, periodontal disease, trigeminal nerve pain, stress 3. The meridians used for the treatment are large intestine, stomach, triple warmer, gallbladder and small intestine 4. The most frequently used acupuncture point for the treatment are Hapkok(LI3), Naejong(S44), Hyopko(S6), Igan(LI2), Sohae(H3), Yanggok(SI5), Hagan(S7), Taeyong(S5), Samgan(LI3), Kokehi(LI11) 5. The most frequently used moxibustion for the treatment are Sungjang(CV24), Yolgyol(L7), Kyonu(LI15), Taeyon(L9), Hapkok(LI3) 6. In the superior dental pain there commonly used the acupuncture point of stomach meridian, triple warmer meridian, gallbladder meridian in the inferior dental pain there commonly used the acupuncture point of large intestine meridian. 7. The most frequently used acupuncture point for the superior dental pain are Naejong(ST44), Yanggok(SI5), Chongnyong(G17), Kakson(TE20), In the inferior detal pain there are Taeyong(S5), Hapkok(LI3), Igan(LI2), Sangyang(LI1), Samgan(LI3) 8. In the treatment of dental pain The Acupuncture therapy utilized the division of region are the Erzhen therapy(耳針療法), the Touzhen therapy(頭鍼療法), the Shouzhen therapy(手鍼療法), the Zuzhen therapy(足鍼療法), the Bizhen therapy(鼻針療法), the Wanhuaizhen therapy 9. In dental pain the other therapy are the Taozhen therapy(陶鍼療法), the Pifuzhen therapy(皮膚針療法), the Dianzhen therapy(電鍼療法), the Yaozhen therapy(藥針療法).

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.91-117
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• 2022

The number of depressed patients in Korea and around the world is rapidly increasing every year. However, most of the mentally ill patients are not aware that they are suffering from the disease, so adequate treatment is not being performed. If depressive symptoms are neglected, it can lead to suicide, anxiety, and other psychological problems. Therefore, early detection and treatment of depression are very important in improving mental health. To improve this problem, this study presented a deep learning-based depression tendency model using Korean social media text. After collecting data from Naver KonwledgeiN, Naver Blog, Hidoc, and Twitter, DSM-5 major depressive disorder diagnosis criteria were used to classify and annotate classes according to the number of depressive symptoms. Afterwards, TF-IDF analysis and simultaneous word analysis were performed to examine the characteristics of each class of the corpus constructed. In addition, word embedding, dictionary-based sentiment analysis, and LDA topic modeling were performed to generate a depression tendency classification model using various text features. Through this, the embedded text, sentiment score, and topic number for each document were calculated and used as text features. As a result, it was confirmed that the highest accuracy rate of 83.28% was achieved when the depression tendency was classified based on the KorBERT algorithm by combining both the emotional score and the topic of the document with the embedded text. This study establishes a classification model for Korean depression trends with improved performance using various text features, and detects potential depressive patients early among Korean online community users, enabling rapid treatment and prevention, thereby enabling the mental health of Korean society. It is significant in that it can help in promotion.

• Journal of Life Science
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• v.29 no.2
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• pp.181-190
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• 2019

The purpose of this study was to acquire the active compounds of Anisi stellati fructus (ASF) and to analyze the genes and diseases it targets, focusing on its antibacterial effects using a system pharmacological analysis approach. Active compounds of ASF were obtained through the Traditional Chinese Medicine Systems Pharmacology (TCMSP) Database and Analysis Platform. This contains the pharmacokinetic properties of active compounds and related drug-target-disease networks, which is a breakthrough in silico approach possible at the network level. Gene information of targets was gathered from the UnitProt Database, and gene ontology analysis was performed using the David 6.8 Gene Functional Classification Tool. A total of 201 target genes were collected, which corresponded to the nine screened active compounds, and 47 genes were found to act on biological processes related to antimicrobial activity. The representative active compounds involved in antibacterial action were luteolin, kaempferol, and quercetin. Among their targets, Chemokine ligand2, Interleukin-10, Interleukin-6, and Tumor Necrosis Factor were associated with more than three antimicrobial biological processes. This study has provided accurate evidence while saving time and effort to select future laboratory research materials. The data obtained has provided important data for infection prevention and treatment strategies.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.1-11
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• 2023

Breast cancer is the disease that affects women the most worldwide. Due to the development of computer technology, the efficiency of machine learning has increased, and thus plays an important role in cancer detection and diagnosis. Deep learning is a field of machine learning technology based on an artificial neural network, and its performance has been rapidly improved in recent years, and its application range is expanding. In this paper, we propose a DNN-SVM hybrid model that combines the structure of a deep neural network (DNN) based on transfer learning and a support vector machine (SVM) for breast cancer classification. The transfer learning-based proposed model is effective for small training data, has a fast learning speed, and can improve model performance by combining all the advantages of a single model, that is, DNN and SVM. To evaluate the performance of the proposed DNN-SVM Hybrid model, the performance test results with WOBC and WDBC breast cancer data provided by the UCI machine learning repository showed that the proposed model is superior to single models such as logistic regression, DNN, and SVM, and ensemble models such as random forest in various performance measures.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.3
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• pp.661-668
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• 2018

Biomedical signals using skin resistance have different characteristics according to stress diseases. Biological diagnostic devices for diagnosing stress diseases have been developed by using these characteristics, and devices have been developed so that the signals measured by the skin storage meter can be easily analyzed. Experts in the field will look directly at the output signal to determine the likelihood of any stress disorder. However, it is very difficult for a person to accurately determine whether a person to be measured has a stress disorder by analyzing a bio-signal measured by each person to be measured, and the result of the judgment is very likely to be wrong. In order to solve these problems, we implemented the function of determining the signal of a stress disorder by using the machine learning technique. SVM was used as a classification method in consideration of low computing ability of measurement equipment. Training data and test data were randomly generated for each disease using error range 5 based on 13 diseases. Simulation results showed more than 90% decision accuracy. In the future, if the measurement equipment is actually applied to the patients, we can retrain the classifier with the newly generated data.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.507-516
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• 2008

Cardiac disease is the leading cause of death in the world. Quantification of cardiac function is performed by manually calculating blood volume and ejection fraction in routine clinical practice, but it requires high computational costs. In this study, an automatic left ventricle (LV) segmentation algorithm using short-axis cine cardiac MRI is presented. We compensate coil sensitivity of magnitude images depending on coil location, classify edge information after extracting edges, and segment LV by applying region-growing segmentation. We design a weighting function for intensity signal and calculate a blood volume of LV considering partial voxel effects. Using cardiac cine SSFP of 38 subjects with Cornell University IRB approval, we compared our algorithm to manual contour tracing and MASS software. Without partial volume effects, we achieved segmentation accuracy of $3.3mL{\pm}5.8$ (standard deviation) and $3.2mL{\pm}4.3$ in diastolic and systolic phases, respectively. With partial volume effects, the accuracy was $19.1mL{\pm}8.8$ and $10.3mL{\pm}6.1$ in diastolic and systolic phases, respectively. Also in ejection fraction, the accuracy was $-1.3%{\pm}2.6$ and $-2.1%{\pm}2.4$ without and with partial volume effects, respectively. Results support that the proposed algorithm is exact and useful for clinical practice.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.7-14
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• 2021

Tomato crops are highly affected by tomato diseases, and if not prevented, a disease can cause severe losses for the agricultural economy. Therefore, there is a need for a system that quickly and accurately diagnoses various tomato diseases. In this paper, we propose a system that classifies nine diseases as well as healthy tomato plants by applying various pretrained deep learning-based CNN models trained on an ImageNet dataset. The tomato leaf image dataset obtained from PlantVillage is provided as input to ResNet, Xception, and DenseNet, which have deep learning-based CNN architectures. The proposed models were constructed by adding a top-level classifier to the basic CNN model, and they were trained by applying a 5-fold cross-validation strategy. All three of the proposed models were trained in two stages: transfer learning (which freezes the layers of the basic CNN model and then trains only the top-level classifiers), and fine-tuned learning (which sets the learning rate to a very small number and trains after unfreezing basic CNN layers). SGD, RMSprop, and Adam were applied as optimization algorithms. The experimental results show that the DenseNet CNN model to which the RMSprop algorithm was applied output the best results, with 98.63% accuracy.

• Journal of Gastric Cancer
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• v.2 no.2
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• pp.85-90
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• 2002

Purpose: Perforated gastric cancer (PGC) is rare and occurs in $1\∼4\%$ of all gastric cancers. Possible dissemination of tumor cells at the time of perforation of the gastric carcinoma has been a matter of concern. The intraoperative determination of what kind of operation should be done and how extensive the lymphnode dissection should be still remains controversial. The purpose of this study is to evaluate the factors influencing the survival and to determine the optimal treatment for PGC. Materials and Methods: A total of 42 patients were operated on for a perforated gastric carcinoma at Soonchunhyang University Chunan Hospital from 1983 to 2000. the age and the sexes of the patients, the location of perforation, the diameter of perforation, the histologic type of the tumor, the depth of wall invasion, the absence or presence of lymph node metastasis / distant metastasis, the stage of disease, the type of operation, and the outcomes were examined. Statistically significant differences were analyzed by using Fisher's exact test. Results: The stage distributions according to the UICC classification were 1 case of stage I, 6 cases of stage II, 17 cases of stage III, and 11 cases of stage IV. An emergency gastrectomy was done in 26 patients ($61.9\%$), with a 5-yr survival rate of $44\%$. The survival of patients was significantly influenced by the depth of wall invasion, the lymphnode metastasis, distant metastasis, the stage of disease, and the type of operation. Conclusions: an emergency gastrectomy is the treatment of choice for most patients with resectable PGC. Choosing more a optimistic surgical approach for potentially curative cases of PGC should be one way to increase the patient's survival rate.

• Research in Community and Public Health Nursing
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• v.12 no.1
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• pp.278-287
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• 2001

The purpose of this study is to provide with basic information on application of hand acupuncture as a complementary and alternative therapy by giving some recognition of efficiency and effectiveness of hand acupuncture. And so, answers for questionnaires of 290 respondents were used for this research and collected from June 5 through 13, 1999 from adults twenty and over who were participating in the hand acupuncture training program in Seoul and had some direct experiences with hand acupuncture therapy, whatever they had been treated and/or had treated. To secure reliability of measurement tool. Cronbach'a has been calculated and Factor Analysis was done as Validity Analysis of question classification. Demograprucal characteristics of hand acupuncture experienced people and factors related to hand acupuncture experiences are calculated based on the real number and percentage. The degree of recognition of efficiency and effectiveness of hand acupuncture is made as average and standard deviation, while the degree of recognition of efficiency and effectiveness based on general characteristics come from one-way ANOVA. 1. According to socio-demographical analysis. the questioned could be classified firstly as age (40-49 : 32.5%. 30-39 : 24.9%. 50-59 : 21.9%. 60-69 : 14.7%. 20-29 : 6.0%). secondly gender (male 36.6%. female 63.4%). thirdly occupation (housewife: 43.8%. self-employed: 15.5%. company-employee: 14.8%). fourthly education (high school graduate: 41.9%, college graduate: 37.9%), and lastly monthly-income (1 to 2 million: 51.4%. 2 to 3 million: 20,3%) 2, As for the general aspects related to hand acupuncture. 80,0% of the respondents answered almost zero for the monthly average number of visit to hospital and 15.5% responded 1 to 2 visits, 6,2% of the respondents is complaining of a disorder of digestive system. 19,0% circulatory disease, 10.7% bad nervous system. By utilizing hand acupuncture, 84% of the questioned have following experiences in curing diseases: digestive system 47.3%, circulatory system 9.3%, nervous system 8.3%, 54,1% are curing 1 to 2 and 10.3% 3 to 4 patients on a daily basis with hand acupuncture. Research on the demerits of giving medical treatment with hand acupuncture shows 23,8% are feeling economic burden. 16.6% difficulty of learning and 16.2% weak theoretical backgrounds. 3. Among the efficiency recognition, possibility of general application is average 4,29 and simple treatment is 4,19. economic merits 4.36. possibility of establishment with supplementary and alternative medicine 4.17, medical effectiveness 4.09. 4, As a result of demographical analysis on the efficiency and effectiveness of hand acupuncture therapy, it appears that the recognition of efficiency based on occupation and the recognition of effectiveness based on monthly income are most significant to be noticed. In an orderly fashion. government-employee, self-employed, company-employee. and then housewife have perceived hand acupuncture very efficiently, And those who recognize hand acupuncture to be most effective are people earn 1 million to 2 million won a month, 5. The efficiency(p = .003) and effectiveness (p= .049) of hand acupuncture therapy by number of visit to hospital were statiscally significant, and effectiveness of hand acupuncture therapy by disease exist was statiscally significant (p= .033).