• Title/Summary/Keyword: Medical model

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Automatic Extraction of Liver Region from Medical Images by Using an MFUnet

  • Vi, Vo Thi Tuong;Oh, A-Ran;Lee, Guee-Sang;Yang, Hyung-Jeong;Kim, Soo-Hyung
    • Smart Media Journal
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    • v.9 no.3
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    • pp.59-70
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    • 2020
  • This paper presents a fully automatic tool to recognize the liver region from CT images based on a deep learning model, namely Multiple Filter U-net, MFUnet. The advantages of both U-net and Multiple Filters were utilized to construct an autoencoder model, called MFUnet for segmenting the liver region from computed tomograph. The MFUnet architecture includes the autoencoding model which is used for regenerating the liver region, the backbone model for extracting features which is trained on ImageNet, and the predicting model used for liver segmentation. The LiTS dataset and Chaos dataset were used for the evaluation of our research. This result shows that the integration of Multiple Filter to U-net improves the performance of liver segmentation and it opens up many research directions in medical imaging processing field.

Three-dimensional Active Shape Model for Object Segmentation (관심 객체 분할을 위한 삼차원 능동모양모델 기법)

  • Lim, Seong-Jae;Ho, Yo-Sung
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.335-336
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    • 2006
  • In this paper, we propose an active shape image segmentation method for three-dimensional(3-D) medical images using a generation method of the 3-D shape model. The proposed method generates the shape model using a distance transform and a tetrahedron method for landmarking. After generating the 3-D model, we extend the training and segmentation processes of 2-D active shape model(ASM) and improve the searching process. The proposed method provides comparative results to 2-D ASM, region-based or contour-based methods. Experimental results demonstrate that this algorithm is effective for a semi-automatic segmentation method of 3-D medical images.

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Factors Affecting the Daily Charges in Patients with Lumbar Discectomy - A Comparison of linear regression versus Multilevel Modeling (요추 추간판제거술 환자의 일일진료비에 영향을 주는 요인 - 선형회귀와 다수준 선형회귀 모델의 비교)

  • Kim, Sang-Mi;Lee, Hae-Jong
    • Korea Journal of Hospital Management
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    • v.20 no.1
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    • pp.53-64
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    • 2015
  • Our objective was to evaluate differences in linear regression versus multilevel(cross-level interaction model) modeling for affecting factors lumbar discectomy. The data were used in 2011 patients with HIRA sample data. Total number of analysis is 3,641 patients and 248 hospitals. The results of research model showed that the type and location of the hospital-level factors were significant. However, all factors of patient-level were similar in the two models. Therefore, it requires the selection of an appropriate model for a more accurate analysis of the influencing factors in the daily medical charge.

The Development of an Instructional Model of Holographic Standardized Patient-based Learning for Enhancing Clinical Reasoning skill in Undergraduate Healthcare Education

  • Youngjoon Kang;Yun KANG;Hyeonmi Hong;Woosuck Lee
    • International Journal of Advanced Culture Technology
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    • v.11 no.1
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    • pp.18-26
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    • 2023
  • The use of holographic standardized patient (HSP) with mixed reality can provide students with the opportunity to enhance clinical reasoning skills. This is still relatively new, so there is a lack of guidelines for educators. Thus, we aimed to develop the instructional model of HSP-based education, for enhancing clinical reasoning skills in undergraduate healthcare education, which could systematically guide educators in designing and implementing HSP-based teaching and learning activities appropriately. Using a design and development research, a theoretically constructed initial mode in this study was iteratively improved and underwent validation through expert review and model usability test. Features of the model were discussed, along with theoretical and practical implications and suggestions for further research.

A Canine Model of Tracheal Stenosis Using Nd-YAG Laser (Nd-YAG laser를 이용한 기관협착 동물모델의 개발)

  • Kim, Jhin-Gook;Suh, Gee-Young;Chung, Man-Pyo;Kwon, O-Jung;Suh, Soo-Won;Kim, Ho-Joong
    • Tuberculosis and Respiratory Diseases
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    • v.52 no.1
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    • pp.54-61
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    • 2002
  • Background: Tracheal stenosis is an urgent but uncommon disease. Therefore, primary care clinicians have limited clinical experience. Animal models of a tracheal stenosis can be used conveniently for the learning, teaching, and developing new diagnostic and therapeutic modalities for tracheal stenosis. Recently, a canine model of a tracheal stenosis was developed using a Nd-YAG laser. To describe the methods and results of developed animal model, we performed this study. Methods : Six Mongrel dogs were generally anesthetized and the anterior 180 degree of tracheal cartilage of the animal was photo-coagulated using a Nd-YAG laser. The animals were bronchoscopically evaluated every week for 4 weeks and a pathologic evaluation was also made. Results : Two weeks after the laser coagulation, the trachea began to stenose and the stenosis progressed through 4 weeks. All animals suffered from shortness of breath, wheezing, and weight loss in the 3 weeks after the laser treatment, and two died of respiratory failure just before the fourth week. The gross pathologic findings showed the loss of cartilage and a dense fibrosis, which resulted in a fibrous stricture of the trachea. Microscopy also showed that the fibrous granulation tissue replaced destroyed cartilage. Conclusion : The canine model can assist in the understanding and development of new diagnostic and therapeutic modalities for tracheal stenosis.

Accuracy of one-step automated orthodontic diagnosis model using a convolutional neural network and lateral cephalogram images with different qualities obtained from nationwide multi-hospitals

  • Yim, Sunjin;Kim, Sungchul;Kim, Inhwan;Park, Jae-Woo;Cho, Jin-Hyoung;Hong, Mihee;Kang, Kyung-Hwa;Kim, Minji;Kim, Su-Jung;Kim, Yoon-Ji;Kim, Young Ho;Lim, Sung-Hoon;Sung, Sang Jin;Kim, Namkug;Baek, Seung-Hak
    • The korean journal of orthodontics
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    • v.52 no.1
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    • pp.3-19
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    • 2022
  • Objective: The purpose of this study was to investigate the accuracy of one-step automated orthodontic diagnosis of skeletodental discrepancies using a convolutional neural network (CNN) and lateral cephalogram images with different qualities from nationwide multi-hospitals. Methods: Among 2,174 lateral cephalograms, 1,993 cephalograms from two hospitals were used for training and internal test sets and 181 cephalograms from eight other hospitals were used for an external test set. They were divided into three classification groups according to anteroposterior skeletal discrepancies (Class I, II, and III), vertical skeletal discrepancies (normodivergent, hypodivergent, and hyperdivergent patterns), and vertical dental discrepancies (normal overbite, deep bite, and open bite) as a gold standard. Pre-trained DenseNet-169 was used as a CNN classifier model. Diagnostic performance was evaluated by receiver operating characteristic (ROC) analysis, t-stochastic neighbor embedding (t-SNE), and gradient-weighted class activation mapping (Grad-CAM). Results: In the ROC analysis, the mean area under the curve and the mean accuracy of all classifications were high with both internal and external test sets (all, > 0.89 and > 0.80). In the t-SNE analysis, our model succeeded in creating good separation between three classification groups. Grad-CAM figures showed differences in the location and size of the focus areas between three classification groups in each diagnosis. Conclusions: Since the accuracy of our model was validated with both internal and external test sets, it shows the possible usefulness of a one-step automated orthodontic diagnosis tool using a CNN model. However, it still needs technical improvement in terms of classifying vertical dental discrepancies.

A Study on Qulity Perceptions and Satisfaction for Medical Service Marketing (의료서비스 마케팅을 위한 품질지각과 만족에 관한 연구)

  • Yoo, Dong-Keun
    • Journal of Korean Academy of Nursing Administration
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    • v.2 no.1
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    • pp.97-114
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    • 1996
  • INSTRODUCTION Service quality is, unlike goods quality, an abstract and elusive constuct. Service quality and its requirements are not easily understood by consumers, and also present some critical research problems. However, quality is very important to marketers and consumers in that it has many strategic benefits in contributing to profitability of marketing activities and consumers' problem-solving activities. Moreover, despite the phenomenal growth of medical service sector, few researchers have attempted to define and model medical service quality. Especially, little research has focused on the evaluation of medical service quality and patient satisfaction from the perspectives of both the provider and the patient. As competition intensifies and patients are demanding higher quality of medical service, medical service quality and patient satisfaction has emerged as a critical research topic. The major purpose of this article is to explore the concept of medical service quality and its evaluation from both nurse and patient perspectives. This article attempts to achieve its purpose by (1)classfying critical service attibutes into threecategories(satisfiers, hygiene factors, and performance factors). (2)measuring the relative importance of need criteria, (3)evaluating SERVPERF model and SERVQUAL model in medical service sector, and (4)identifying the relationship between perceived quality and overall patient satisfaction. METHOD Data were gathered from a sample of 217 patients and 179 nurses in Seoul-area general hospitals. From the review of previous literature, 50 survey items representing various facets of the medical service quality were developed to form a questionnaire. A five-point scale ranging from "Strongly Agree"(5) to "Strongly Disagree"(1) accompanied each statement(expectation statements, perception statements, and importance statements). To measure overall satisfaction, a seven-point scale was used, ranging from "Very Satisfied"(7) to "Very Dissatisfied"(1) with no verbal labels for scale points 2 through 6 RESULTS In explaining the relationship between perceived performance and overall satisfaction, only 31 variables out of original 50 survey items were proven to be statistically significant. Hence, a penalty-reward analysis was performed on theses 31 critical attributes to find out 17 satisfiers, 8 hygiene factors, and 4 performance factors in patient perspective. The role(category) of each service quality attribute in relation to patient satisfaction was com pared across two groups, that is, patients and nurses. They were little overlapped, suggesting that two groups had different sets of 'perceived quality' attributes. Principal components factor analyses of the patients' and nurses' responses were performed to identify the underlying dimensions for the set of performance(experience) statements. 28 variables were analyzed by using a varimax rotation after deleting three obscure variables. The number of factors to be extracted was determined by evaluating the eigenvalue scores. Six factors wereextracted, accounting for 57.1% of the total variance. Reliability analysis was performed to refine the factors further. Using coefficient alpha, scores of .84 to .65 were obtained. Individual-item analysis indicated that all statements in each of the factors should remain. On 26 attributes of 31 critical service quality attributes, there were gaps between actual patient's importance of need criteria and nurse perceptions of them. Those critical attributes could be classified into four categories based on the relative importance of need criteria and perceived performance from the perspective of patient. This analysis is useful in developing strategic plans for performance improvement. (1) top priorities(high importance and low performance) (in this study)- more health-related information -accuracy in billing - quality of food - appointments at my convenience - information about tests and treatments - prompt service of business office -adequacy of accommodations(elevators, etc) (2) current strengths(high importance and high performance) (3)unnecessary strengths(low importance and high performance) (4) low priorities(low importance and low performance) While 26 service quality attributes of SERPERF model were significantly related to patient satisfation, only 13 attributes of SERVQUAL model were significantly related. This result suggested that only experience-based norms(SERVPERF model) were more appropriate than expectations to serve as a benchmark against which service experiences were compared(SERVQUAL model). However, it must be noted that the degree of association to overall satisfaction was not consistent. There were some gaps between nurse percetions and patient perception of medical service performance. From the patient's viewpoint, "personal likability", "technical skill/trust", and "cares about me" were most significant positioning factors that contributed patient satisfaction. DISCUSSION This study shows that there are inconsistencies between nurse perceptions and patient perceptions of medical service attributes. Also, for service quality improvement, it is most important for nurses to understand what satisfiers, hygiene factors, and performance factors are through two-way communications. Patient satisfaction should be measured, and problems identified should be resolved for survival in intense competitive market conditions. Hence, patient satisfaction monitoring is now becoming a standard marketing tool for healthcare providers and its role is expected to increase.

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Construction of Artificial Intelligence Training Platform for Multi-Center Clinical Research (다기관 임상연구를 위한 인공지능 학습 플랫폼 구축)

  • Lee, Chung-Sub;Kim, Ji-Eon;No, Si-Hyeong;Kim, Tae-Hoon;Yoon, Kwon-Ha;Jeong, Chang-Won
    • KIPS Transactions on Computer and Communication Systems
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    • v.9 no.10
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    • pp.239-246
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    • 2020
  • In the medical field where artificial intelligence technology is introduced, research related to clinical decision support system(CDSS) in relation to diagnosis and prediction is actively being conducted. In particular, medical imaging-based disease diagnosis area applied AI technologies at various products. However, medical imaging data consists of inconsistent data, and it is a reality that it takes considerable time to prepare and use it for research. This paper describes a one-stop AI learning platform for converting to medical image standard R_CDM(Radiology Common Data Model) and supporting AI algorithm development research based on the dataset. To this, the focus is on linking with the existing CDM(common data model) and model the system, including the schema of the medical imaging standard model and report information for multi-center research based on DICOM(Digital Imaging and Communications in Medicine) tag information. And also, we show the execution results based on generated datasets through the AI learning platform. As a proposed platform, it is expected to be used for various image-based artificial intelligence researches.

Development of a Hospital Service-based Costing System and Its Application (병원서비스별 원가분석모형의 개발과 적용)

  • 박하영
    • Health Policy and Management
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    • v.5 no.2
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    • pp.35-69
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    • 1995
  • The managerial environment of hospitals in Korea characterized by low levels of medical insurance fees is worsening by increasing government regulations as to the utilization of medical services, rising costs of labor, material, and medical equipments, growing patient expectations concerning the quality of services, and escalating competitions among large hospitals in the market. Hospitals should seek for their survival strategies in this harsh environment and they should have information about costs of their products in doing so. However, it has not been available due to the complexity of the production process of hospital services. The objectives of this study were to develop a service-based cost accounting model and to apply the developed model to a study hospital to obtain cost information of hospital services. A model commonly used for the job-order product cost accounting in the manufacturing industry was modified for the use in hospitals in Korea. Actual costs, instead of standard costs, incurred to produce a unit of services during a given period of time were estimated in the model. Data required to implement the model included financial information, statistics for the allocation of supportive cost center costs to final cost centers, statistics for the allocation of final cost center costs to services, and the volume of each services charged to patients during a study period. The model was executed using data of a university teaching hospital located in Seoul for the fiscal year 1992. Data for financial information, allocation statistics fo supportive service costs, and the volume of services, most of them in electronic form, were available to the study. Data for allocation statistics of final cost center costs were collected in the study. There were 15 types of evaluation and management service, 2, 923 types of technical service, and 2, 608 types of drug and material service charged to patients in the study hospital during the fiscal year 1992. Labor costs of each of seven types of pesonnel, material costs of 611 types of drugs and materials, and depreciation costs of 212 types of medical equipments, miscellaneous costs, and indirect costs incurred in producing a unit of each services were estimated. Medical insurance fees for basic services such as evaluation and management of inpatients and outpatients, injection, and filling prescriptions, and for operating procedures were found to be set lower than costs. Infrequent services which use expensive medical equipments showed negative revenuse as well. On the other hand, fees for services not covered by the insurance such as CT, MRI and Sonogram, and for laboratory tests were higher than costs. This study has a significance in making it possible for a hospital to obtain cost information for all types of services which produced income based on all types of expenses incurred during a given period of time. This information can assist the management of a hospital in finding an effective cost reduction strategy, an efficient service-mix strategy under a given fee structure, and an optimum strategy for within-hospital resource allocations.

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Gene Polymorphism of XRCC1 Arg399Gln and Cervical Carcinoma Susceptibility in Asians: A Meta-analysis Based on 1,759 Cases and 2,497 Controls

  • Liu, Yi-Ting;Shi, Jing-Pu;Fu, Ling-Yu;Zhou, Bo;Wang, Hai-Long;Wu, Xiao-Mei
    • Asian Pacific Journal of Cancer Prevention
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    • v.14 no.1
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    • pp.189-193
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    • 2013
  • Many epidemiological studies in Asian populations have investigated associations between the Arg399Gln gene polymorphism of X-ray repair cross complementing gene 1 (XRCC1) and risk of cervical carcinoma, but no conclusions have been available because of controversial results. Therefore a meta-analysis was conducted for clarification. Relevant studies were identified by searching the Pubmed, Embase, the Web of Science, Cochrane Collaboration's database, Chinese National Knowledge Infrastructure (CNKI), Wanfang database and China Biological Medicinse (CBM) until September, 2012. A total of eight studies were included in the present meta-analysis, which described 1,759 cervical carcinoma cases and 2,497 controls. Odds ratios (ORs) and corresponding 95% confidence intervals (95%CIs) as effect size were calculated by fixed-effect or random-effect models. The overall results indicated that the XRCC1-399G/A polymorphism was marginally associated with cervical carcinoma in Asians: OR (95%CI): 1.16 (1.07, 1.26) in the G/A vs G/G inheritance model, 1.24 (0.87, 1.76)in A/A vs G/G inheritance model, 1.13 (1.01, 1.27) in the dominant inheritance model and 1.18 (0.94, 1.47) in the recessive inheritance model. Subgroup analyses on sample size showed no significant correlation in the small-sample size group but the large-sample size group was consistent with the outcomes of overall meta-analysis. In the subgroup analysis by regions, we only found significant association under the G/A vs G/G inheritance model in the Chinese population. For the non-Chinese populations, no correlation was detected in any genetic inheritance model. In the Asian populations, XRCC1-399G/A gene polymorphism was implied to be associated with cervical carcinoma.