• Child Health Nursing Research
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• v.8 no.3
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• pp.344-356
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• 2002

This study was conducted to analyse the current clinical education of pediatric nursing in baccalaurate nursing program, then to give basic data for enhancing the quality of future clinical education of pediatric nursing. Data were collected through self-reported questionnaire by mail from December 2001 to February 2002. The subjects were 29 schools of 50 baccalaurate nursing education programs. The data were analysed by double raters, researcher and assistant researcher. The results were summarized as follows: 1. Twenty-eight schools had the objectives of the clinical education of pediatric nursing, and 28 schools in pediatric ward, 23 schools in nursery, 22 schools in neonatal intensive care unit(NICU), 15 schools in objectives related to profession by clinical site. 2. Credits on clinical education of pediatric nursing were most 15 schools of 3 credits. 3. The clinical sites were mainly the hospital that sick children were admitted in. 4. The clinical teacher were 9 types including pediatric professor and field nurse. 5. On teacher's role, the professor instructed the case study and conference, and field nurse instructed the patient assignment and nursing procedures. 6. All of schools used explanation and conference as a method of clinical education, 1 or 2 schools used PBL or role play or field study. 7. On clinical education content, most of school included Apgar scoring system, physical examination in newborn assessment, respira- tion maintenance, temperature maintenance, infection prevention, nutrition, and bath in newborn care. 8. On clinical education content, most of school included care of incubator, phototheraty, infusion, gavage feeding and how to use the instruments in NICU. Eighteen schools included attachment promotion, and 20 schools case study. 9. On clinical education content, most of school included a checklist of nursing procedures, case study, assessment of growth and development in pediatric ward and other sites. 10.There were various evaluation types in scores, measuring items. In conclusion, the results of this study revealed that there were some discrepancy in the objectives and contents, clinical sites on hospital focused, teacher's role, and diversity of measurement items and ratings in clinical education of pediatric nursing. There is a need for a standardization of content, clinical site, and evaluation tool to improve a quality of clinical education of pediatric nursing based on this study.

• Korean Journal of Oriental Medicine
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• v.17 no.2
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• pp.121-127
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• 2011

Objectives : In the clinical field, it is important to understand the factors that have effects on a certain disease or symptom. For this, many researchers apply Data Mining method to the clinical data that they have collected. One of the efficient methods for Data Mining is decision tree induction. Many researchers have studied to find the best split criteria of decision tree; however, various split criteria coexist. Methods : In this paper, we applied several split criteria(Information Gain, Gini Index, Chi-Square) to Sasang constitutional clinical information and compared each decision tree in order to find optimal split criteria. Results & Conclusion : We found BMI and body measurement factors are important factors to Sasang constitution by analyzing produced decision trees with different split measures. And the decision tree using information gain had the highest accuracy. However, the decision tree that produced highest accuracy is changed depending on given data. So, researcher have to try to find proper split criteria for given data by understanding attribute of the given data.

• Journal of Physiology & Pathology in Korean Medicine
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• v.35 no.5
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• pp.132-138
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• 2021

Artificial intelligence technology sheds light on new ways of innovating acupuncture research. As acupoint selection is specific to target diseases, each acupoint is generally believed to have a specific indication. However, the specificity of acupoint selection may be not always same with the specificity of acupoint indication. In this review, we propose that the specificity of acupoint indication can be inferred from clinical data using reverse inference. Using forward inference, the prescribed acupoints for each disease can be quantified for the specificity of acupoint selection. Using reverse inference, targeted diseases for each acupoint can be quantified for the specificity of acupoint indication. It is noteworthy that the selection of an acupoint for a particular disease does not imply the acupoint has specific indications for that disease. Electronic medical record includes various symptoms and chosen acupoint combinations. Data mining approach can be useful to reveal the complex relationships between diseases and acupoints from clinical data. Combining the clinical information and the bodily sensation map, the spatial patterns of acupoint indication can be further estimated. Interoperable medical data should be collected for medical knowledge discovery and clinical decision support system. In the era of artificial intelligence, machine learning can reveal the associations between diseases and prescribed acupoints from large scale clinical data warehouse.

• Journal of Sensor Science and Technology
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• v.32 no.6
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• pp.378-385
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• 2023

Human biosignals provide essential information for diagnosing diseases such as dementia and Parkinson's disease. Owing to the shortcomings of current clinical assessments, noninvasive solutions are required. Machine learning (ML) on wearable sensor data is a promising method for the real-time monitoring and early detection of abnormalities. ML facilitates disease identification, severity measurement, and remote rehabilitation by providing continuous feedback. In the context of wearable sensor technology, ML involves training on observed data for tasks such as classification and regression with applications in clinical metrics. Although supervised ML presents challenges in clinical settings, unsupervised learning, which focuses on tasks such as cluster identification and anomaly detection, has emerged as a useful alternative. This review examines and discusses a variety of ML algorithms such as Support Vector Machines (SVM), Random Forests (RF), Decision Trees (DT), Neural Networks (NN), and Deep Learning for the analysis of complex clinical data.

• Journal of Biomedical Engineering Research
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• v.26 no.2
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• pp.65-71
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• 2005

The main obstacles for adopting a mobile health information system to existing hospital information system are the redundancy of clinical data and the additional workload for implementing the new system. To obtain a seamless communication and to reduce the workload of implementation, an easy and simple implementation strategy is required. We propose a mobile clinical information system (MobileMed) which is specially designed for the easy implementation. The key elements of MobileMed are a smart interface, an HL7 message server, a central clinical database (CCDB), and a web server. The smart interface module transfers the key information to the HL7 message server as new clinical tests data is recorded in the existing laboratory information system. The HL7 message server generates the HL7 messages and sends them to the CCDS. As a central database the CCDS collects the HL7 messages and presents them to the various mobile devices such as PDA. Through this study we might conclude that the architecture for the mobile system will be efficient for real-time data communication, and the specially designed interface will be an easy tool for implementing the mobile clinical information system.

• Korean Journal of Clinical Pharmacy
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• v.26 no.2
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• pp.181-186
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• 2016

Background: There has been on increasing emphasis on the importance of monitoring the safety of participants in a clinical trial to protect patients and maintain the integrity of the trial. The independent data monitoring committee (IDMC) has become common component of randomized clinical trials in recent years. Methods: It is important to consider the implications of different approaches that are being used in various countries. IDMC guidelines in Korea, US, and Europe were reviewed and compared to provide the objective, composition and operation of IDMC in detail. Results: IDMC is a group of experts in related subject are as who perform interim data monitoring to make a recommendation to the sponsor or organizer regarding appropriateness of trial continuation and the need for modifications of the trial. Independence of IDMC is preferred in order to minimize influence of factors unrelated to scientific, medical and ethical considerations that should underlie decision-making. Conclusion: IDMC has become an increasingly important component of clinical trials in recent years. Practical operating procedures need to be developed considering the future regulatory status of data monitoring committees.

• The Journal of Korean Medicine
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• v.30 no.1
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• pp.40-50
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• 2009

Objectives: The clinical document forms, a format for collecting clinical data, is the most fundamental object of standardization. Doctors must have a mutual understanding of the clinical chart. Methods: Clinical document forms were developed by investigating existing conditions in hospitals and conducting demand surveys, doing literature research, and seeking expert advice for the improvement of version 1.0. In addition, an organization of a network of 19 Oriental medical doctors and nurses, 190 patients, and users of collected and assessed data was formed to come up with version 2.0. Results: The overall format was divided into different portions that the patient, nurse, and doctor must fill out, respectively. The patient's section consists of demographic data, lifestyle details, history, and symptoms. The data to be supplied by the nurse include the patient's vital signs and anthropometric parameters. As for the doctors, they are to supply data regarding the patient's palpitation, the detailed symptoms of the patient's head, ophthalmological and otorhinolaryngological symptoms (mouth), respiration, circulatory organ and chest conditions, digestive-organ conditions (thirst), neuropsychiatric conditions, reproductive system, musculoskeletal system, skin (depilation), etc. Conclusions: Common clinical chart development is the prior question to Traditional Korean Medicine standardization. A web-based clinical document format should be developed to support diagnosis and treatment, and furthermore EMR (electronic medical record system) and EHR (electronic health record) developed. Clinical information could be shared through a network of medical institutions and be useful Traditional Korean Medicine for evidence-based medicine.

• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.200-201
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• 2005

• The Journal of Korean Academic Society of Nursing Education
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• v.11 no.2
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• pp.222-231
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• 2005

Purpose: The purpose of this study was to identify the relationship between critical thinking disposition and clinical competency of nursing students. Method : The sample consisted of 151 nursing students, who have ever had clinical practice. Data were collected by self reporting questionnaire for 13 days from April 18-30, 2005. The data were analyzed by descriptive statistics, t-test, ANOVA, Duncan test, Pearson Correlation Coefficient with SPSS Programs. Result : The result of this study were as follows : 1. The total mean score of critical thinking dispositions in the nursing students was moderately(3.50). There was a statistically significant difference in critical thinking disposition according to satisfaction with the nursing major(F=5.563, p=.005). 2. The total mean score of clinical competency in the nursing students was slightly high(3.37). There was a statistically significant difference in clinical competency according to adaptation with the nursing major(F=5.202, p=.007), satisfaction with clinical practice(F=3.172, p=.045). 3. A significant positive correlation between critical thinking disposition and clinical competency was founded(r= .421, p<.000). Conclusion : In conclusion, this study revealed that critical thinking disposition influences clinical competence. Therefore, the finding of this study may provide significant basic data for nursing education and nursing practice.

• Korean Journal of Clinical Pharmacy
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• v.23 no.1
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• pp.26-32
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• 2013

Objective: This study was to define the clinical effect on the clinical decision support system (CDSS) for prescribing antibiotics integrated with the order communication system in a National Hospital. Method: We extracted data collected before integrating the CDSS of 4,406 adult patients in 2007 and data collected after integrating the CDSS of 4,278 adult patients in 2009. These patients were 50.4% and 45.2% of all patients admitted in 2007 and 2009, respectively. The clinical effect was defined as the proportion of prescribed antibiotics, the length of antibiotics use, and the DDDs (defined daily doses) of antibiotics per 1,000 patient-days using these retrospective data. Results: There were a significant change in the proportion of patient prescribed penicillins with extended spectrum (OR=0.55, p=001), penicillins included beta-lactamase inhibitors (OR=0.75, p<.001), 3rd cephalosporin (OR=1.47, p<.001). The mean of the length of antibiotics use was decreased statistically from $6.09{\pm}5.48$ to $5.85{\pm}5.51$ days (p=.003). The DDD of glycopeptides was decreased from 24.43 DDD to 19.55 DDD per 1000 patient-days. The DDD of 3rd cephalosporins was also decreased from 15.88 to 11.65. Conclusion: Therefore, the clinical decision support system for prescribing antibiotics was effective for the clinical outcomes.