Expert systems emerged during early 1970s have become one of the most important innovations in computer science. They actively work in various areas and achieve a big success especially in medical domain. It is to be difficult to obtain reliable recognitions about each diagnosis that has common characteristics and to manage data about over 140 nursing diagnoses by using existing Nursing Diagnosis System with artificial neural network. But a rule-based approach has been studied to automate diagnosis and is more effective that nursing diagnosis depends on objective data and has more common characteristics. In this paper, Nursing Diagnosis System was built with a rule-based approach due to the above reasons. Nursing Diagnosis System is implemented by using rules of production system, a kind of knowledge representation technique based on standardized nursing care plans. The ten nursing diagnoses, found most frequently from the patients on medical-surgical wards were determined to develop Nursing Diagnosis System. To verify the usefulness of Nursing Diagnosis System was tested with 80 patient's data. A diagnosis was judged correct if the system and the nursing experts agreed on diagnosing. The nursing experts evaluated 100 percents of the system's diagnosis was deemed correct. Judging from the results given above, the system seems highly reliable. In this work, I show that it can contribute to clinical application of nursing process as another nursing tool.
Diagnosis ; Expert Systems* ; Humans ; Nursing Diagnosis* ; Nursing Process ; Nursing* ; Patient Care Planning

With growing need in the field, the application of computers in nursing has been frequently studied to improve the quality of nursing care in Korea. But the development of useful clinical programs has not received adequate alternatives. The aim of this study is to compare of two Nursing Diagnosis Systems - Neutral Network and Expert System. The simulated output of each Nursing Diagnosis System and the Judgment from the researcher and two professors of nursing were comparatively examined. The misdiagnosis rate of Nursing Diagnosis System using the Neural Network was nine percent, while the Nursing Diagnosis System using the Expert System showed consistency with those three experts in every aspect. Accordingly, the result of this study demonstrated the possibility of application of a nursing diagnosis system as another nursing tool.
Diagnostic Errors ; Expert Systems* ; Judgment ; Korea ; Nursing Care ; Nursing Diagnosis* ; Nursing*

BACKGROUND: Osteoporosis is the most common metabolic bone disorder. Osteoporosis has emerged as a leading public health problem with elderly persons and its detection is important for prevention and treatment of fracture. this population-based study was conducted to evaluate the prevalence and risk factors of osteoporosis in the elderly women. METHODS: One hundred thirty eight women aged 60 years or older in rural area were investigated with questionnaires and measurements of height, weight. Bone mineral density(BMD) measurements of lumbar spine and femoral neck were made with dual energy X-ray absorptiometry(DEXA). The World Health Organization criteria for diagnosis of osteoporosis using the manufacturer's young adult population mean and our study young population mean have been applied. Our study's young adult population mean was derived using normal premenopausal 37 women aged 30~45 years. RESULTS: The prevalence of osteoporosis was 45.7% for lumbar spine, 13.0% for femoral neck by the manufacture's young adult mean and 63.0% and 34.8% by our study young adult population mean, respectively. Weight and smoking were associated with lumbar spine BMD. Age was associated with femoral neck BMD. CONCLUSION: Our data suggest that the prevalence of osteoporosis is dependant on reference population mean and measurement site.
Aged* ; Diagnosis ; Female ; Femur Neck ; Humans ; Osteoporosis* ; Prevalence* ; Public Health ; Surveys and Questionnaires ; Risk Factors ; Smoke ; Smoking ; Spine ; World Health Organization ; Young Adult

Polyarteritis nodosa is systemic necrotizing vasculitis of medium and small-sized arteries and results in variable manifestations due to ischemia of the involving organs. Diagnosis can either be made pathologically by demonstrating necrotizing vasculitis of arteries or angiographycally by demonstrating small arterial aneurysm. We experienced a case of PAN with dilated cardiomyopathy, confirmed by clinical feature, renal biopsy, angiography and echocardiography.
Aneurysm ; Angiography ; Arteries ; Biopsy ; Cardiomyopathy, Dilated* ; Diagnosis ; Echocardiography ; Ischemia ; Polyarteritis Nodosa* ; Vasculitis

No abstract available.

No abstract available.
Humans

PURPOSE: This microethnographic study was performed to understand the survival experiences of patients after surgical resection of colorectal cancer. METHODS: In-depth interviews of seven male and six female patients with colorectal cancer were conducted after being observed. Digital-audio recordings of the interviews were transcribed verbatim and then qualitatively analyzed. RESULTS: The survival journeys of patients with colorectal cancer surgery were described as 'born again after going through an altered self-image'. This consists of 4 phases: 'Confrontation of the cancer diagnosis', 'Fierce compliance', 'Leveling off', and 'Born again'. Their self-images were significantly altered subsequent to confronting their cancer diagnosis. While they were in the phase of fierce compliance, patients were introverted from the outside world, but upon receiving help from a substantial supportive system including family, health professionals, peer patients, and religion, their internalized self-image was reinforced. This would significantly boost the patients' morale. Finally they felt born again with an emotional and spiritual self-image. CONCLUSION: Nursing intervention should be differentiated and specified according to the specific phase of the long term colorectal cancer survival journey. Colorectal cancer patients should be provided with a specialized nursing program to improve their self-images.
Colorectal Neoplasms* ; Compliance ; Diagnosis ; Female ; General Surgery ; Health Occupations ; Humans ; Life Change Events ; Male ; Morale ; Nursing ; Self Concept ; Survivors

PURPOSE: The purpose of the study was to assess the quality of meta-analyses on nursing published in South Korea. METHODS: Relevant meta-analyses were identified through searches of the National Assembly Library, KISS (Korean Studies Information Service System), and the DBpia and RISS4U databases from 1990 to May 2013. Quality assessments were conducted using AMSTAR, a validated tool for assessing the quality of systematic reviews. RESULTS: Forty-two meta-analyses were included in this study. Twenty-nine published between 1990 and 2010, and 13, between 2011 and May 2013. Two high quality studies and 11 moderate quality studies were published in the latter period. The mean score for the reviews was 5.61 (range 3-10); 11 studies were rated as low quality, 29 as moderate quality, and two as high quality. CONCLUSION: Although an improvement in the quality of meta-analyses conducted by nursing researchers in South Korea was observed across the study period, the study results indicate a need to use of more rigorous research methods when conducting systematic reviews or meta-analyses.
Databases, Factual ; Humans ; Nursing Research/*standards ; Peer Review, Research ; Republic of Korea

With the rapid growth of research and recognition about usefulness and importnace of the Nursing Diagnosis, the demand for application of Nursing Diagnosis has never been stronger. But in clinical field, not many nurses has used Nursing Diagnosis. Especially, nursing student have a difficulty to use Nursing Diagnosis because it demands for high level of capability of analyzing collected data and combining with relevant references. Therefore. this research has developed Nursing Diagnosis Self-learning Program using Back-propagating Neutral Network Model which is based on 98 surgery patients' data for nursing student. The twenty-six nursing diagnoses based on NANDA Taxonomy with 189 cases' reports and aid of 8 nursing experts wee determined to develop the program. To verify the usefulness of Nursing Diagnosis Self-learning Program constructed with the fully trained neural nets, the Program was tested with 70 real patients' data. The simulated output of program was compared with the judgement of the researcher and of two experts of nursing. The misdiagnosis rate of this program was eleven percent. This Program needs input of Signs and Symptoms, risk factors and 'related to' factors and also input the nursing diagnoses which a student selects. And than prints out two types of diagnoses. One is from the system and the other is what the student inputed. And the student makes the final diagnosis by refering the two types of diagnoses. Finally, the program prints out the completed diagnosis which problem combines with etiology in the diagnosis producing module. The program helps students to improve her capacity related to use Nursing Diagnosis.
Classification ; Diagnosis ; Diagnostic Errors ; Humans ; Neural Networks (Computer)* ; Nursing Diagnosis* ; Nursing* ; Risk Factors ; Students, Nursing

No abstract available.
Adenocarcinoma, Mucinous* ; Child* ; Colon* ; Humans ; Mucins*