• 임상간호연구
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• 제28권2호
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• pp.198-209
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• 2022

Purpose: The purpose of the study was to shorten the KPCS-1 (Korean Patient Classification System-1) for predicting nursing care need level and to explore whether the patients can be clustered by their acuity and dependency. Methods: The participants were inpatients in two surgical wards and two internal medicine wards at a teritory hospital during 14 days investigations. The KPCS-1 was evaluated once a day for all inpatients and 2,082 cases of data from a total of 411 patients were analyzed. Results: The items were reducted from 50 items to 26 items by partial least squares analysis and expert review. Through factor analysis, it was confirmed that hygiene, diet, elimination, and exercise were categorized as dependence factors. Patients were clustered with low acuity/low dependency (average score: 7.68±2.81/1.05±1.33), high acuity/low dependency (average score: 17.20±4.15/1.94±2.40), medium acuity/high dependency (average score: 13.56±5.30/9.66±2.64) through cluster analysis. The total score of the three groups for their nursing care needs was 8.73±3.36, 19.14±5.74, and 23.24±6.31 in order, and the results showed a statistically significant difference (F=1712.12, p<.001). Conclusion: The shortening of the KPCS-1 and the new criteria for categorizing patients according to acuity and dependence will increase clinical utility and be useful for manpower assignment criteria in detail.

• 대한의용생체공학회:의공학회지
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• 제44권3호
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• pp.167-175
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• 2023

Chest PA is the basic examination of radiographic imaging. Moreover, Chest PA's demands are constantly increasing because of the Increase in respiratory diseases. However, it is not meeting the demand due to problems such as a shortage of radiological technologist, sexual shame caused by patient contact, and the spread of infectious diseases. There have been many cases of using artificial intelligence to solve this problem. Therefore, the purpose of this research is to build an artificial intelligence dataset of Chest PA and to find a posture evaluation method. To construct the posture dataset, the posture image is acquired during actual and simulated examination and classified correct and incorrect posture of the patient. And to evaluate the artificial intelligence posture method, a posture estimation algorithm is used to preprocess the dataset and an artificial intelligence classification algorithm is applied. As a result, Chest PA posture dataset is validated with in over 95% accuracy in all artificial intelligence classification and the accuracy is improved through the Top-Down posture estimation algorithm AlphaPose and the classification InceptionV3 algorithm. Based on this, it will be possible to build a non-face-to-face automatic Chest PA examination system using artificial intelligence.

• 한국간담췌외과학회지
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• 제27권3호
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• pp.251-257
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• 2023

Backgrounds/Aims: This is a retrospective analysis of whether the 8th edition American Joint Committee on Cancer (AJCC) was a significant improvement over the 7th AJCC distal extrahepatic cholangiocarcinoma classification. Methods: In total, 111 patients who underwent curative resection of mid-distal bile duct cancer from 2002 to 2019 were included. Cases were re-classified into 7th and 8th AJCC as well as clinicopathological univariate and multivariate, and Kaplan-Meier survival curve and log rank were calculated using R software. Results: In patient characteristics, pancreaticoduodenectomy/pylorus preserving pancreaticoduodenectomy had better survival than segmental resection. Only lymphovascular invasion was found to be significant (hazard ratio 2.01, p = 0.039) among all clinicopathological variables. The 8th edition AJCC Kaplan Meier survival curve showed an inability to properly segregate stage I and IIA, while there was a large difference in survival probability between IIA and IIB. Conclusions: The 8th distal AJCC classification did resolve the anatomical issue with the T stage, as T1 and T3 showed improvement over the 7th AJCC, and the N stage division of the N1 and N2 category was found to be justified, with poorer survival in N2 than N1. Meanwhile, in TMN staging, the 8th AJCC was able differentiate between early stage (I and IIA) and late stage (IIB and III) to better explain the patient prognosis.

• 간호행정학회지
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• 제5권3호
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• pp.513-524
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• 1999

The shortage of nursing personnel was become one of the most serious problems in operating pediatric oncology nursing unit which was the first pediatric oncology nursing unit in Korea. The purpose of this study was to estimate the optimal number of nursing personnel by calculating nursing care hours. The subjects were 13 staff nurses and inpatients of pediatric oncology nursing unit at Seoul National University Hospital during the period of May 20, 1996, to June 2, 1996. The number of nurses' duty was 132, the number of patients treated was 1288 for these 2 weeks. The tools used for this study were pediatric patient classification indexes and direct & indirect care indexes. Each nurse measured the time that they spent for their activities by self record under the supervision of their nurse manager. The method used to calculate the number of nursing personnel was multiplication of the average number of nursing care hours per patient per day with the number of patients. Percentage, average, t-test, F-test were used for data analysis. The results of this study were as follows : 1) The distribution of patient class : Class I & II none, Class III 86.8%. Class IV 12.9% 2) Direct nursing care hours for a patient per shift according to patient classification: Class III : 27.64 minutes, Class IV : 54.64 minutes The average direct nursing service hours for a patient per shift(3 shift) was 31.54 minutes(94.62 m/day). The average indirect nursing service hours for each patient per duty(3 shift) is 21.3 minutes (63. 91 m/day). 3) The average nursing hours for a patient per duty was 52.80 minutes(2.64h/day). 4) The group of administering medications in direct care activities showed the highest percentage (38.9%). Checking vital signs among observation took the most time am.ong each direct care activity (6.88 minutes for a patient per duty). 5) Charting took the most time of each indirect care activity(52.53 minutes/ duty/nurse). 6) The average personal time per duty is 29.40 minutes, which 'was below 30 minutes of this hospital regulations. 7) The average nursing hours that a nurse provided for a duty was 8.60 hours, which meant that a nurse worked 1.10 hours overtime. 8) Standardizing to a 33 bed to a unit, 17 nurses were needed at the present nursing level.

• 의료법학
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• 제18권2호
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• pp.3-46
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• 2017

의사의 설명의무는 의사가 환자에게 이미 시행한 의료행위, 시행 중인 의료행위 및 장래에 시행할 의료행위와 환자의 요양상 수칙에 관하여 적극적 체계적으로 진술함으로써 환자가 그 내용을 인식하게 할 법적 의무를 총칭한다. 이 의무는 환자의 알 권리에 대응하는 보고성 설명의무, 환자의 동의권 거절권에 대응하는 기여성 설명의무, 요양지도성 설명의무로 나뉜다. 설명의무를 분류하는 것은 각각의 기능과 법적 성질이 다르고, 법적 성질이 다름에 따라 그 위반 시의 효과, 특히 손해배상책임의 대상과 범위가 달라지기 때문이다. 이 주제에 관하여 우리나라에서는 지난 40년 가까운 기간 동안 많은 이론의 발전이 있었고, 그를 토대로 대법원 판결의 논리도 상당히 정치하게 전개되어 왔다. 그러나 여전히 학계와 실무계 일각에서는 용어와 개념의 혼동, 학설과 판례 논리에 대한 이해 부족을 목격하게 되고, 심지어 대법원 판결문 내의 전후 문맥에서 그리고 관련 있는 복수의 판례 사이에서 논리와 이론의 불일치를 발견하게 되는 것이 사실이다(이것은 합리적 근거와 설득력을 지닌 견해의 분립을 지적하는 것이 아니다). 위와 같은 견해와 문제의식을 기초로 해서, 의사가 부담하는 설명의무의 기능별 분류와 법적 성질 및 그 위반 시의 효과를 우리나라 학설과 판례를 중심으로 분석 정리한다.

• Imaging Science in Dentistry
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• 제32권3호
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• pp.129-134
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• 2002

Purpose : To implement the database system of oral and maxillofacial radiological images using a commercial medical image management software with personally developed classification code. Materials and methods : The image database was built using a slightly modified commercial medical image management software, Dr. Image v.2.1 (Bit Computer Co., Korea). The function of wild card '*' was added to the search function of this program. Diagnosis classification codes were written as the number at the first three digits, and radiographic technique classification codes as the alphabet right after the diagnosis code. 449 radiological films of 218 cases from January, 2000 to December, 2000, which had been specially stored for the demonstration and education at Dept. of OMF Radiology of Dankook University Dental Hospital, were scanned with each patient information. Results: Cases could be efficiently accessed and analyzed by using the classification code. Search and statistics results were easily obtained according to sex, age, disease diagnosis and radiographic technique. Conclusion : Efficient image management was possible with this image database system. Application of this system to other departments or personal image management can be made possible by utilizing the appropriate classification code system.

• 대한의용생체공학회:의공학회지
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• 제31권1호
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• pp.40-49
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• 2010

A rule weight -based fuzzy classification model is proposed to analyze the patterns of admission-discharge of patients as a previous research for differential diagnosis of dyspnea. The proposed model is automatically generated from a labeled data set, supervised learning strategy, using three procedure methodology: i) select fuzzy partition regions from spatial distribution of data; ii) generate fuzzy membership functions from the selected partition regions; and iii) extract a set of candidate rules and resolve a conflict problem among the candidate rules. The effectiveness of the proposed fuzzy classification model was demonstrated by comparing the experimental results for the dyspnea patients' data set with 11 features selected from 55 features by clinicians with those obtained using the conventional classification methods, such as standard fuzzy classifier without rule weights, C4.5, QDA, kNN, and SVMs.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2011년도 한국컴퓨터종합학술대회논문집 Vol.38 No.1(C)
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• pp.195-197
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• 2011

This research deals with an issue of preventive medicine in bioinformatics. We can diagnose liver conditions reasonably well to prevent Liver Cirrhosis by classifying liver disorder patients into fatty liver and high risk groups. The classification proceeds in two steps. Classification rules are first built by clustering five attributes (MCV, ALP, ALT, ASP, and GGT) of blood test dataset provided by the UCI Repository. The clusters can be formed by the K-mean method that analyzes multi dimensional attributes. We analyze the properties of each cluster divided into fatty liver, high risk and normal classes. The classification rules are generated by the analysis. In this paper, we suggest a method to diagnosis and predict liver condition to alcoholic patient according to risk levels using the classification rule from the new results of blood test. The K-mean classifier has been found to be more accurate for the result of blood test and provides the risk of fatty liver to normal liver conditions.

• 대한치과보철학회지
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• 제55권2호
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• pp.198-204
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• 2017

악안면부의 결손은 선천적으로 결손을 가지고 있거나 외상이나 수술적인 절제 등에 의한 후천적 원인에 의해 발생할 수 있다. 특히 구강 내 결손을 가진 환자 중 상악의 결손과 연관되어 있는 경우가 높은 비중을 차지하고 있으며 보철적 치료의 필요성이 높다. 하악의 부분적 결손을 가질 경우 기능적 회복에 상당한 한계점을 보이나 양측 턱관절이 정상적으로 남아 있을 경우 국소의치를 이용한 악안면 보철물을 제작함으로써 양호한 결과를 기대할 수 있다. 본 증례의 환자는 58세 남자 환자로서 안면부 총상으로 인한 구개부 및 좌측 하악 구치부 결손을 가진 분으로 obturator와 하악 RPD 재제작을 위해 내원하였다. 환자의 상악 결손 범위는 Aramany 분류법 Class IV에 해당되는 상태이며, 하악은 Cantor와 Curtis 분류법 Type V resection 상태이다. 상, 하악의 우측 구치부가 잔존하였으나, 수술 후 악골 변형으로 인해 서로 교합되지 않았으며 치주상태 불량으로 인한 동요도도 존재하는 상태였다. Obturator의 유지를 위해 잔존 지대치를 최대한 활용하였고 안정적인 교합이 형성되도록 치아를 배열하였다. 하악 RPD는 하악 절제술로 변형된 연조직에 적합하도록 제한된 범위를 피개하는 RPD를 제작하였다. 이에 환자분의 저작, 연하, 발음 기능이 많이 개선되었으며 만족할 만한 결과를 보여주어 본 증례를 발표하는 바이다.

• 한국의학물리학회:학술대회논문집
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• 한국의학물리학회 2004년도 제29회 추계학술대회 발표논문집
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• pp.59-63
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• 2004

IAEA에서 제공한 선량기준은 서양 사람을 기준으로 개발된 것이어서 우리 한국 사람에게는 맞지 않고, 상대적으로 우리나라의 환자선량은 적으리라 예상된다. 따라서 선량기준을 따로 개발해야할 필요가 있다. 그래서 본 연구팀은 병원협회에 등록되어 있는 종합병원 278개를 대상으로 환자 피폭에 대한 설문조사를 실시하였다. 설문회수율은 57.9%였으며 각 병원에서의 촬영조건을 기초로 NDD법을 이용하여 환자 피폭선량을 계산하였고 설문지를 분석한 결과를 보고한다.