• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.06a
• /
• pp.289-292
• /
• 2007

우리가 다른 이들과 만나 대화하는 것은 극히 평범한 일이다. 하지만 대화뿐만이 아니라 의사소통마저도 힘들어하는 이들이 있다. 이들은 언어 장애를 가진 이들이다. 언어 장애에는 태어나면서부터 장애를 가지는 선천적 장애와 사고와 질병으로 인한 후천적 장애가 있다. 그 중 후천적 장애는 언어장애와 더불어 신체적 장애를 가진 이들이 있다. 이들을 본 논문에서는 중증 언어 장애인이라고 분류하였다. 중증 언어 장애인의 장애정도를 크게 글자 표현이 불가능한 상태로부터 4가지 단계로 나뉠 수 있다. 글자 표현이 불가능하지만 개체 선택이 가능한 1단계, 손 혹은 발을 이용하여 가부 결정만 가능한 2단계, 지체를 이용하여 표현이 불가능한 3단계, 그리고 마지막 4단계가 3단계의 표현마저도 불가능하여 의사소통이 전혀 불가능한 상태이다. 사고로 인한 후천적 장애인 경우 위의 4가지 단계중 하나의 단계에서 머물러 있지만, 루게릭병과 같은 병은 위의 4가지 단계를 몇 년에 걸쳐서 진행되기 때문에 일반적인 장비로써는 이 들과의 의사소통이 불가능하다. 본 논문에서는 위의 1,2,3단계의 중증 언어 장애인을 대상으로 그들이 의사소통을 정확하고 신속하게 전달하기 위해서 어떠한 인터페이스를 사용하는 것이 효과적인 방법에 대해 논해보고, 향후 발전될 방향에 대해서 그 방향을 제시하였다.

• The Korean Journal of Rehabilitation Nursing
• /
• v.2 no.2
• /
• pp.225-233
• /
• 1999

The purpose of this study is to determine the need of education about BSE for the medical members, to survey about the performance and the knowledge of BSE in patients who operated on subtotal and total mastectomy and to compare the regularity of BSE with the severity of breast cancer. The subjects were 163 patients with operated on mastectomy who participated were interviewed in the S university Hospital. The collected data were analyzed by descriptive statistics and t-test, One-way ANOVA and Pearson Correlation with SPSSWIN program. Results were obtained as follows: 1. There was no statistical difference between in the regular group of the mammography and the regular BSE group(F=0.558, P=0.458). 2. There was statistical difference between the method of detection and the severity of the breast cancer(F=3.359, P=0.011). 3. There was statistical difference between regularity of the BSE and the severity of breast cancer(F=3.301, P=0.019). 4. There was showed higher severity of the breast cancer in the elderly patients(r=0.172, P=0.019). 5. There was showed higher severity of the breast cancer in the lower educational level(r=-0.170, P=0.033). According to this study need to the development of the educational program about the BSE and the future research about the regular BSE of the high risk group in the breast cancer.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.6
• /
• pp.2668-2676
• /
• 2011

In order to analyze the variation in length of stay(LOS) of injury inpatients, we developed severity-adjusted LOS model using Korean National Discharge In-depth Injury Survey data of Center for Disease Control. Appling this model, we calculated predicted values and, after standardizing LOS using the differences from the actual values, analyzed the variation in LOS. Major factors affecting severity-adjusted LOS of injury inpatients were found to be severity, surgery(or no surgery), age, injury mechanism and channel of hospitalization. Result of analysis of the differences between the actual values and predicted values adjusted by decision tree model suggested that there were statistically significant differences by hospital size(number of beds), type of insurance and location of institution. In order to reduce the variation in LOS, efforts should be exerted in developing nationwide treatment protocol, inducing medical institutions to utilize it, and furthermore systematically evaluating it to reduce the variation continually.

• Journal of the Korea Society of Computer and Information
• /
• v.16 no.1
• /
• pp.175-182
• /
• 2011

This study proposes CAOPI(Computer Aided Organ Prediction Index) system based on APACHE II(Acute Physiology And Chronic Health Evaluation) for classifying disease severity and predicting the conditions of patients' major organs. The existing ICU disease severity evaluation is mostly about calculating risk scores using patients' data at certain points, which has limitations on making precise treatments. CAOPI system is designed to provide personalized treatments by classifying accurate severity degrees of emergency patients, predicting patients' mortality rate and scoring the conditions of certain organs.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.8
• /
• pp.2134-2140
• /
• 2009

The purpose of this study is to compare relationship among pulmonary function, dyspnea, and health-related quality of life in patients with COPD. The instruments were used FEV1(%), the Baseline Dyspnea Index(BDI), the Medical Research Council Scale(MRCS), and the St. George's respiratory questionnaire(SGRQ). Dyspnea of patients with moderate and severe stage were deeper than one of patients with mild stage(BDI F=5.452, p=.007; MRCS F=4.925, p=.011). And health-related quality of life of patients with severe stage were poorer than one of patients with mild stage(F=3.778, p=.030). There were significant, but weak, correlations between scores of the BDI(r=.471), the MRCS(r=-.403), the SGRQ(r=-.476) and FEV1. There were strong correlations between scores of the BDI(r=-.752), the MRCS(r=.645) and the SGRQ. And FEV1 didn't correlated with the BDI, the MRCS, and the SGRQ scores in patient of moderate stage and severe stage. But there were also strong correlations between the BDI(r=-.719), the MRCS(r=.607) and the SGRQ in patient of moderate stage and severe stage. Specially, correlation between the BDI and the SGRQ were higher than one between the MRCS and the SGRQ. In conclusion, Using the BDI for evaluation of the subjective dyspnea with objective pulmonary functional test in patients with COPD, it will able to grasp the health-related quality of life.

• Child Health Nursing Research
• /
• v.21 no.3
• /
• pp.227-235
• /
• 2015

Purpose: The purpose of this study was to investigate disease prevalence, parent's educational needs, and disease management according to severity of respiratory infections in early childhood. Methods: Participants for this study were 173 mothers whose child was admitted to I university hospital in Seoul and whose child was an infant or toddler. Data were collected from December, 17, 2014 to February, 15, 2015 using self-report structured questionnaires. Data were analyzed using IBM/SPSS 21.0 program. Results: There were significant differences in the severity of respiratory infection according to neonatal admission due to dyspnea, feeding type, atopic dermatitis in the infant or allergic disease in father and siblings. Parent's educational needs for the severe respiratory infection group were higher than for the non-severe group. Parent's disease management for the severe respiratory infection group was lower than the non-severe group. Conclusion: As important care factors in neonatal admissions include dyspnea, cow milk feeding, eczema, family history of allergies, parent's educational needs and disease management, they should be considered when caring for young children with respiratory infections and their parents.

• Phonetics and Speech Sciences
• /
• v.14 no.4
• /
• pp.45-56
• /
• 2022

This paper proposes an optimal methodology for automatically diagnosing and predicting the severity of the chronic kidney disease (CKD) using patients' utterances. In patients with CKD, the voice changes due to the weakening of respiratory and laryngeal muscles and vocal fold edema. Previous studies have phonetically analyzed the voices of patients with CKD, but no studies have been conducted to classify the voices of patients. In this paper, the utterances of patients with CKD were classified using the variety of utterance types (sustained vowel, sentence, general sentence), the feature sets [handcrafted features, extended Geneva Minimalistic Acoustic Parameter Set (eGeMAPS), CNN extracted features], and the classifiers (SVM, XGBoost). Total of 1,523 utterances which are 3 hours, 26 minutes, and 25 seconds long, are used. F1-score of 0.93 for automatically diagnosing a disease, 0.89 for a 3-classes problem, and 0.84 for a 5-classes problem were achieved. The highest performance was obtained when the combination of general sentence utterances, handcrafted feature set, and XGBoost was used. The result suggests that a general sentence utterance that can reflect all speakers' speech characteristics and an appropriate feature set extracted from there are adequate for the automatic classification of CKD patients' utterances.

• Journal of Acupuncture Research
• /
• v.21 no.1
• /
• pp.211-225
• /
• 2004

목적 : 류마티스 관절염 환자의 골 파괴에 중요한 역할을 하는 것으로 알려진 Matrix Metalloproteinase-1(MMP-1) 유전자의 단일 염기 다형성을 분석하고, 나아가 봉독약침 치료에 대한 반응과의 연관성을 조사하기 위하여 본 연구를 시행하였다. 방법 : 미국류마티스학회의 류마티스 관절염 기준에 해당하는 122명의 한국인 류마티스 관절염 환자와 건강한 92명의 대조군을 대상으로 pyrosequencing 방법을 이용하여 MMP-1 유전자의 -519 위치의 다형성을 비교 분석하였으며, 류마티스 관절염 환자군을 다시 유전자 유형에 따라 동통 관절수, 종창 관절수, 조기 강직, 통증 강도, 삶의 질 평가도구인 HAQ, 환자 및 의사의 전반적 질병상태 평가, ESR, CRP 등의 항목을 치료 전후 평가하여 비교 분석하였다. 결과 : 1. 류마티스 환자군과 건강한 대조군간에 MMP-1 유전자의 단일 염기 다형성의 유전자형의 분포와 대립유전자 발현 빈도에 통계적으로 유의한 차이가 나타났으며, 이는 MMP-1 유전자 다형성이 한국인 류마티스 관절염 환자의 질병 감수성과 관련이 있음을 추정할 수 있다. 2. 각 유전자형 그룹간 치료전 질병의 중증도 평가에서 임상 평가와 혈액의 급성 염증 반응물질 평가에서 통계적으로 유의한 차이는 없었다. 3. 급성 염증 반응의 지표인 ESR과 CRP level의 봉독약침 치료 전후 변화는 MMP-1의 유전자 다형성과 유의한 연관이 없었다. 4. 각 유전자형 그룹간의 치료 전후 질병 호전도 비교에서, AA 유전자형이 종창 관절수 평가에서 더나은 호전을 보였으며, 다른 모든 평가에서는 통계적으로 유의한 차이가 없었으며, 향후 관련 유전자와의 연관성 연구가 필요하다고 사료된다.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.11
• /
• pp.126-136
• /
• 2018

The purpose of this study was to develop a severity-adjustment model for predicting mortality in acute stroke patients using machine learning. Using the Korean National Hospital Discharge In-depth Injury Survey from 2006 to 2015, the study population with disease code I60-I63 (KCD 7) were extracted for further analysis. Three tools were used for the severity-adjustment of comorbidity: the Charlson Comorbidity Index (CCI), the Elixhauser comorbidity index (ECI), and the Clinical Classification Software (CCS). The severity-adjustment models for mortality prediction in patients with acute stroke were developed using logistic regression, decision tree, neural network, and support vector machine methods. The most common comorbid disease in stroke patients were hypertension, uncomplicated (43.8%) in the ECI, and essential hypertension (43.9%) in the CCS. Among the CCI, ECI, and CCS, CCS had the highest AUC value. CCS was confirmed as the best severity correction tool. In addition, the AUC values for variables of CCS including main diagnosis, gender, age, hospitalization route, and existence of surgery were 0.808 for the logistic regression analysis, 0.785 for the decision tree, 0.809 for the neural network and 0.830 for the support vector machine. Therefore, the best predictive power was achieved by the support vector machine technique. The results of this study can be used in the establishment of health policy in the future.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.4
• /
• pp.1739-1750
• /
• 2012

This study was to develop the assessment of medical service outcome using administration data through compared with hospital standardized mortality ratios(HSMR) in various hospitals. This study analyzed 63,664 cases of Hospital Discharge Injury Data of 2007 and 2008, provided by Korea Centers for Disease Control and Prevention. We used data mining technique and compared decision tree and logistic regression for developing risk-adjustment model of in-hospital mortality. Our Analysis shows that gender, length of stay, Elixhauser comorbidity index, hospitalization path, and primary diagnosis are main variables which influence mortality ratio. By comparing hospital standardized mortality ratios(HSMR) with standardized variables, we found concrete differences (55.6-201.6) of hospital standardized mortality ratios(HSMR) among hospitals. This proves that there are quality-gaps of medical service among hospitals. This study outcome should be utilized more to achieve the improvement of the quality of medical service.