• Korean Journal of Adult Nursing
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• v.24 no.4
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• pp.358-369
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• 2012

Purpose: This study was performed to compare the costs of nursing interventions implemented for the obstetrical and gynecological patients using Korean Reimbursement System and ABC codes system developed in the US for costing out interventions performed by health care professional. Methods: First, the narrative data on nursing interventions were extracted from electronic medical record system of a tertiary university and mapped with Nursing Intervention Classification (NIC) by two researchers until 100% consent was reached. Narrative nursing interventions mapped with NIC were then remapped with ABC codes system using the electronic program developed in the research. The mapping data were analyzed with real numbers, frequency, percentage, mean, and standard deviation. Results: More nursing interventions were mapped with ABC codes than Korean reimbursement system. Total of 97 different types of narrative interventions could be mapped with NIC, 43 NIC interventions could be reimbursed by ABC code but only 16 NIC interventions were reimbursed by Korea Reimbursement System. Conclusion: Korean medical insurance fee system needs amendment to include more comprehensively interventions performed by nurses which are very important to patient outcomes. Further study is needed to develop strategies to costing out nursing interventions.

• 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.

• Journal of Korean Neurosurgical Society
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• v.49 no.6
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• pp.367-369
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• 2011

Angiocentric glioma was recently recognized as a distinct clinicopathological entity in the 2007 World Health Organization classification of tumors of the central nervous system. Typically, it presents with seizure in children and young adults. However, our patient did not have a history of seizure. Seizure did not occur up to 6 months after operation. Although it usually does not have calcification brain magnetic resonance imaging in our patient showed T1-hyperintense and T2-hypointense signals with calcification.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.284-310
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• 2024

Identifying clinical pathways for disease diagnosis and treatment process recommendations are seriously decision-intensive tasks for health care practitioners. It requires them to rely on their expertise and experience to analyze various categories of health parameters from a health record to arrive at a decision in order to provide an accurate diagnosis and treatment recommendations to the end user (patient). Technological adaptation in the area of medical diagnosis using AI is dispensable; using expert systems to assist health care practitioners in decision-making is becoming increasingly popular. Our work architects a novel knowledge-based recommender system model, an expert system that can bring adaptability and transparency in usage, provide in-depth analysis of a patient's medical record, and prescribe diagnostic results and treatment process recommendations to them. The proposed system uses a set of parallel discrete fuzzy rule-based classifier systems, with each of them providing recommended sub-outcomes of discrete medical conditions. A novel knowledge-based combiner unit extracts significant relationships between the sub-outcomes of discrete fuzzy rule-based classifier systems to provide holistic outcomes and solutions for clinical decision support. The work establishes a model to address disease diagnosis and treatment recommendations for primary lung disease issues. In this paper, we provide some samples to demonstrate the usage of the system, and the results from the system show excellent correlation with expert assessments.

• Journal of Korean Academy of Nursing
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• v.26 no.1
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• pp.177-193
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• 1996

For the purpose of integrating nursing diagnosis into the nursing curriculum, a descriptive survey research was done using the inductive method with questionnaires and a literature review. Research subjects included nurse educators, textbooks of adult nursing published in Korea, and the course outline for adult nursing used in one college of nursing. The Results show that there was common agreement on 39 nursing diagnosis which should be in cluded in the adult nursing curriculum, textbooks of adult nursing, and patient care on the medical-surgical units. The two existing nursing diagnosis classification systems(NANDA and Gordon's Human Response Patterns) show different basic frameworks and difficulties were discovered in integration of nursing diagnosis into the curriculum. To develop a conceptual framework for a nursing diagnosis classification system, diagnosis were classified into three categories ; health promotion, high risk problem, and actual problem on the basis of the framework used in adult nursing textbooks and Gordon's 11 Functional Health Patterns. Subconcepts for actual problems were classified as ; activity and rest, nutrition and elimination, perception and coordination, stress and coping. Progress in this study supports further development of a conceptual framework of nursing based on a nursing diagnosis classification system, from which improvement in nursing education and clinical practice can be expected.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2004.11a
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• pp.59-63
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• 2004

IAEA's Guidance Levels have been provided for Western people to the end. Guidance levels lower than the IAEA'S will be necessary in view of korean people's proportions. Therefore, We need to develope the standard doses for korean people. And we conducted a nationwide survey of patient dose from x-ray examinations in korea. 278 institutions were selected from Members Book of Korean Hospital Association. The valid response rate was approximately 57.9%. Doses were calculated from the questionnaires by NDD method. The results were as follows; 1) General radiographic equipments were 43%, fluoroscopic equipments 29%, dental equipments 13%, CT units 8% and mamographic units 7%. 2) According to classification by rectification way, three-phase equipments were 30%, inverter-type generators 29%, single- phase equipments 26%, unknown units 6%. 3) According to classification by receptor system, film-screen types were 46%, CR types 27%, OR types18% and unknown types 9%. 4) The number of examinations were chest 48%, spine 17% and abdomen 13%. 5) Patient doses were head AP 3.1 mGy, abdomen AP 3.5 mGy and chest PA 0.4 mGy.

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.1
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• pp.97-103
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• 2009

The status and the property of a tongue are the important indicators to diagnose one's health like physiological and clinicopathological changes of inner organs. However, the tongue diagnosis is affected by examination circumstances like a light source, patient's posture, and doctor's condition. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, classifying tongue coating is inevitable but difficult since the features like color and texture of the tongue coatings and substance have little difference, especially in the neighborhood on the tongue surface. The proposed method has two procedures; the first is to acquire the color table to classify tongue coatings and substance by automatically separating coating regions marked by oriental medical doctors, decomposing the color components of the region into hue, saturation and brightness and obtaining the 2nd order discriminant with statistical data of hue and saturation corresponding to each kind of tongue coatings, and the other is to apply the tongue region in an input image to the color table, resulting in separating the regions of tongue coatings and classifying them automatically. As a result, kinds of tongue coatings and substance were segmented from a face image corresponding to regions marked by oriental medical doctors and the color table for classification took hue and saturation values as inputs and produced the classification of the values into white coating, yellow coating and substance in a digital tongue diagnosis system. The coating regions classified by the proposed method were almost the same to the marked regions. The exactness of classification was 83%, which is the degree of correspondence between what Oriental medical doctors diagnosed and what the proposed method classified. Since the classified regions provide effective information, the proposed method can be used to make an objective and standardized diagnosis and applied to an ubiquitous healthcare system. Therefore, the method will be able to be widely used in Oriental medicine.

• Journal of Multimedia Information System
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• v.3 no.2
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• pp.35-42
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• 2016

Electrocardiogram (ECG) signal gives a clear indication whether the heart is at a healthy status or not as the early notification of a cardiac problem in the heart could save the patient's life. Several methods were launched to clarify how to diagnose the abnormality over the ECG signal waves. However, some of them face the problem of lack of accuracy at diagnosis phase of their work. In this research, we present an accurate and successive method for the diagnosis of abnormality through Discrete Wavelet Transform (DWT), QRS complex detection and Support Vector Machines (SVM) classification with overall accuracy rate 95.26%. DWT Refers to sampling any kind of discrete wavelet transform, while SVM is known as a model with related learning algorithm, which is based on supervised learning that perform regression analysis and classification over the data sample. We have tested the ECG signals for 10 patients from different file formats collected from PhysioNet database to observe accuracy level for each patient who needs ECG data to be processed. The results will be presented, in terms of accuracy that ranged from 92.1% to 97.6% and diagnosis status that is classified as either normal or abnormal factors.

• Journal of Korean Academy of Nursing Administration
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• v.16 no.1
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• pp.73-85
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• 2010

Purpose: This study was to construct a useful nursing language system on military nursing field. Method: Military hospital nursing records were analyzed using NANDA(North American Nursing Diagnosis Association), NIC(Nursing Interventions Classification), and NOC(Nursing Outcomes Classification) systems. All kinds of nursing statements from 80 sets of orthopedics inpatient's records were deduced. All nursing statements were mapped to 167 NANDA diagnoses, 433 NIC interventions, and 260 NOC outcomes. Result: 14,744 nursing statements were extracted. Among the extracted nursing statements, 11.75% were linked with NANDA diagnosis, 83.62% were connected with NIC intervention, and 0.96% was tied to NOC outcome. 3.66% of nursing statements were not linked with NANDA-NIC-NOC system. In the nursing statements, 18 diagnoses of NANDA, 63 interventions of NIC, 8 outcomes of NOC were used. Conclusions: The majority of those nursing statements focused on nursing intervention of the nursing process; few nursing plans or goals were found in nursing records. Therefore, it's difficult to make the nursing process network with the nursing statements. Documenting nursing records using a nursing process will contribute to strengthen nursing practice in patient care and to develop nursing as science. Continuous further researches related to nursing records are needed to provide basic data for developing nursing language system and nursing record system.

• The Journal of Korean Academy of Prosthodontics
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• v.44 no.2
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• pp.243-249
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• 2006

Statement of problem: It is important to have a correct presurgical treatment plan before any implant surgery. It must contain substantial information about the patient concerned. However, the standard classification only notifies the dentist about various structural, pathological and physiological dimensions Due to diverse structure of the jaw bone, current standard classification does not tell spatial dimensions of the available bone for implant insertion sites. Purpose of study: The purpose of this study is to report the establishment of the systematic implant treatment plan and its clinical treatment using $Implan^(R)$ program which is based on ASCIi-classification that is available for future diagnosis and scale of treatment and for systematic implant insertion. Results: By assisting the systemic measurement of the available alveolus dimension during implant surgery, it was easy to set initial implant treatment plan. Conclusion: Using $Implan^(R)$ program which is based on ASCIi-classification system that allows the establishment of systemic implant treatment plan and successful clinical performance, it was possible to establish the founding or initial implant treatment plan , the acquisition of information, and the systematization of documentation.