• Journal of Physiology & Pathology in Korean Medicine
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• v.36 no.2
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• pp.73-78
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• 2022

Since Traditional Korean medicine (TKM) doctors use various knowledge systems during treatment, diagnosis results may differ for each TKM doctor. However, it is difficult to explain all the reasons for the diagnosis because TKM doctors use both explicit and implicit knowledge. In this study, an upgraded random forest (RF)-based evaluation tool was proposed to extract clinical knowledge of TKM doctors. Also, it was confirmed to what extent the professor's clinical knowledge was delivered to the trainees by using the evaluation tool. The data used to construct the evaluation tool were targeted at 106 people who visited the Sasang Constitutional Department at Kyung Hee University Korean Medicine Hospital at Gangdong. For explicit knowledge extraction, four TKM doctors were asked to express the importance of symptoms as scores. In addition, for implicit knowledge extraction, importance score was confirmed in the RF model that learned the patient's symptoms and the TKM doctor's constitutional determination results. In order to confirm the delivery of clinical knowledge, the similarity of symptoms that professors and trainees consider important when discriminating constitution was calculated using the Jaccard coefficient. As a result of the study, our proposed tool was able to successfully evaluate the clinical knowledge of TKM doctors. Also, it was confirmed that the professor's clinical knowledge was delivered to the trainee. Our tool can be used in various fields such as providing feedback on treatment, education of training TKM doctors, and development of AI in TKM.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.35 no.7
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• pp.9-25
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• 2017

In this paper, we surveyed state-of-the-art health and wellness platforms. The motivation of this paper is to review the state-of-the-art health and wellness platforms and their maturity with respect to adoption of latest enabling technologies. The is review is classified into four categories: healthcare systems, AI-assisted healthcare, wellness platforms, and open source health and wellness initiatives. From this comprehensive review, it can be stated that the contemporary healthcare systems are well-adopting wellness due to the concentration shift towards prevention. Thus, the gap between health and wellness is slowly yet carefully entering gray area. Where both the domains can freely invoke each other's services, and supporting enabling technologies. Furthermore, the biomedical researchers and physicians are no longer carrying the myopic views of trusting their knowledge for diagnosis. AI-assisted technologies based on machine learning and big data are influencing today's prognosis with trust and confidence.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.999-1008
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• 2023

Early prediction of chronic diseases such as diabetes is an important issue, and improving the accuracy of diabetes prediction is especially important. Various machine learning and deep learning-based methodologies are being introduced for diabetes prediction, but these technologies require large amounts of data for better performance than other methodologies, and the learning cost is high due to complex data models. In this study, we aim to verify the claim that DNN using the pima dataset and k-fold cross-validation reduces the efficiency of diabetes diagnosis models. Machine learning classification methods such as decision trees, SVM, random forests, logistic regression, KNN, and various ensemble techniques were used to determine which algorithm produces the best prediction results. After training and testing all classification models, the proposed system provided the best results on XGBoost classifier with ADASYN method, with accuracy of 81%, F1 coefficient of 0.81, and AUC of 0.84. Additionally, a domain adaptation method was implemented to demonstrate the versatility of the proposed system. An explainable AI approach using the LIME and SHAP frameworks was implemented to understand how the model predicts the final outcome.

• Journal of Oral Medicine and Pain
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• v.18 no.2
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• pp.81-96
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• 1993

In order to evaluate the prognosis of conservative treatment for Craniomandibular Disorders, 127 patients were subjected at the Dept. of Oral Medicine, Pusan National University Hospital from 1983 through 1991. All the changes of patients' symptoms and related factors were analyzed before treatment, after treatment and at follow-up examination by means of subjective and objective symptom indicies (Ai, AAI, SDS, Di, CDS, MCO). 1. All the indices were reduced and MCO became increased at follow-up examination (p<0.01). 2. As the duration after treatment became longer, all the indices became reduced and MCO became increased. 3. There were no significant differences in index scores according to sex and age. 4. Long-term patients showed higher index scores and lower MCO than short-term patients(p<0.01). 5. Chronic group showed higher index scores and lower MCO than acute group (p<0.05). 6. Macrotrauma group showed higher index scores and lower MCO than microtrauma group (p<0.05) 7. While muscle group showed the lowest MCO, muscle and joint group showed the highest index scores (p<0.01). 8. The long-term success rate of conservative treatment was more than 80% (p<0.01)

• Smart Media Journal
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• v.12 no.5
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• pp.81-87
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• 2023

In this paper, accidents in high-voltage overhead distribution lines, which provide stable power supply in the power system, cause inconvenience in life and disruption of production of companies. 22.9 [kV] high-voltage overhead power distribution lines aim to improve reliability and stability, such as damage caused by rain, snow, wind, etc., or electric shock prevention. Therefore, in order to prevent wire disconnection accidents due to deterioration of electrical conductivity or tensile strength due to corrosion of overhead distribution lines, it is necessary to prevent unexpected accidents in the future through regular inspection and repair. In order to diagnose deterioration due to corrosion of distribution lines, a diagnostic system (measuring instrument) is installed on the wires to monitor the condition of the wires. The manager on the ground receives the measured data through ZigBee wireless communication, controls the diagnosis system through the diagnosis system program, and grasps the condition of the overhead distribution line through the measured data and photographed photos, and predicts the life of the wire along with the visual inspection method. developed a program.

• The Journal of Korean Medicine
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• v.44 no.4
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• pp.136-149
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• 2023

Objectives: Facial diagnosis is an important part of clinical diagnosis in traditional East Asian Medicine. In this paper, we proposed a model to quantitatively classify cold sensitivity using a fully automated facial image analysis system. Methods: We investigated cold sensitivity in 452 subjects. Cold sensitivity was determined using a questionnaire and the Cold Pattern Score (CPS) was used for analysis. Subjects with a CPS score below the first quartile (low CPS group) belonged to the cold non-sensitivity group, and subjects with a CPS score above the third quartile (high CPS group) belonged to the cold sensitivity group. After splitting the facial images into train/validation/test sets, the train and validation set were input into a convolutional neural network to learn the model, and then the classification accuracy was calculated for the test set. Results: The classification accuracy of the low CPS group and high CPS group using facial images in all subjects was 76.17%. The classification accuracy by sex was 69.91% for female and 62.86% for male. It is presumed that the deep learning model used facial color or facial shape to classify the low CPS group and the high CPS group, but it is difficult to specifically determine which feature was more important. Conclusions: The experimental results of this study showed that the low CPS group and the high CPS group can be classified with a modest level of accuracy using only facial images. There was a need to develop more advanced models to increase classification accuracy.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.800-807
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• 2022

This study aims to review the use of graph databases in construction research. Based on the diagnosis of the current research status, a future research direction is proposed. The use of graph databases in construction research has been increasing because of the efficiency in expressing complex relations between entities in construction big data. However, no study has been conducted to review systematically the status quo of graph databases. This study analyzes 42 papers in total that deployed a graph model and graph database in construction research, both quantitatively and qualitatively. A keyword analysis, topic modeling, and qualitative content analysis were conducted. The review identified the research topics, types of data sources that compose a graph, and the graph database application methods and algorithms. Although the current research is still in a nascent stage, the graph database research has great potential to develop into an advanced stage, fused with artificial intelligence (AI) in the future, based on the active usage trends this study revealed.

• Journal of Korean Academy of Nursing Administration
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• v.7 no.3
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• pp.425-437
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• 2001

This reserch was to develop database software in order to handle a lot of clinical nursing data with nursing diagnoses, related factors, defining characteristics, nursing interventions, nursing activities and nursing outcomes. MS Access2000 and SQL was selected to use a general purpose database logic with an efficiency. MS Visual Basic 6.0 was used to construct the circumstance of Graphic User Interface. The Linkage Database of abdominal surgery patients was constructed from the clinical data and questionnaire. This database system could add related factors, defining characteristics, nursing activities in the database and analyze the statistical results through Access query. In the final stage, end-users satisfaction analysis using 5 points Likert scale was dong with the response of using the database system. The accuracy/trustworthiness of the database system was verified with the highest average scores as 4.42 and also, the efficiency as 4.21, user friendly function as 4.1.

• Advances in pediatric surgery
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• v.7 no.1
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• pp.64-67
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• 2001

It has been widely accepted that complete surgical resection of hepatoblastoma is essential for long-term survival. But unfortunately less than 50 % of hepatic tumors in children can be totally removed at the time of diagnosis. This report is to present the experience of successful resection of hepatoblastoma after concurrent radiotherapy with transarterial chemoinfusion in a child. We believe this modality of treatment enables complete resection of unresectable hepatoblastoma. which is resistant to the systemic chemotherapy.

• Advances in pediatric surgery
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• v.8 no.1
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• pp.1-5
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• 2002

Diagnosing Hirschsprung's disease is a clinical challenge. Hirschsprung's disease should be considered in any child who has a history of constipation dating back to the newborn period. We examined diagnostic methods and their results retrospectively in 37 neonates and infants who underwent both barium enema and anorectal manometry for the diagnosis of Hirschsprungs disease at Asan Medical Center between January 1999 and April 2001. Two radiologists and a surgeon repeatedly reviewed both of the diagnostic results. In anorectal manometry, thirty-four studies were in agreement with the definitive diagnosis, giving an overall diagnostic accuracy of 91.9 % (neonate; 100 %, infant; 85.7 %). The accuracy and specificity of barium enema was lower than those of anorectal manometry, but sensitivity was higher. There was no significant difference between the two methods. Both studies showed findings consistent with the final diagnosis. However, discordant results needed further evaluation or close observation to diagnose accurately. We conclude that Hirschsprungs disease should not be diagnosed by only one diagnostic method.