• Title/Summary/Keyword: Medical statistics

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Relationship between Local Extinction Index and Medical Service Uses of Chronic Diseases (지역 소멸위험지수와 지역의 만성질환 의료이용의 관계)

  • Lee, Hyun-Ji;Oh, Jae-Hwan;Kim, Jae-Hyun;Lee, Kwang-Soo
    • Health Policy and Management
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    • v.31 no.3
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    • pp.301-311
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    • 2021
  • Background: This study purposed to analyze the relationship between the local extinction index and medical service uses of chronic diseases. The local extinction index is an indicator of the demographic structure and population aging of the region. Methods: The 2014-2018 statistics of National Health Insurance Corporation and Korean Statistical Information Service data were used for the analysis. First, descriptive statistics were used to analyze the general status of research variables. Second, a panel analysis was performed to analyze the relationship between the local extinction index and medical service uses of chronic diseases (hypertension, diabetes mellitus, periodontal disease, arthritis, mental health, epidemic disease, liver disease). Medical service uses were measured by the number of visits/inpatient days and medical charges of seven chronic diseases. Results: Panel analysis results showed that higher local extinction risks (meaning lower local extinction index) had a positive relationship with the number of visits/inpatient days and medical charges of chronic diseases. But the relationships were varied when the seven chronic diseases were analyzed separately. Conclusion: This study showed a significant relationship between the local demographic structure and medical service uses of chronic disease. Analyzing the local demographic structure will be an essential prerequisite step for implementing appropriate regional health care policies.

Frequentist and Bayesian Learning Approaches to Artificial Intelligence

  • Jun, Sunghae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.16 no.2
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    • pp.111-118
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    • 2016
  • Artificial intelligence (AI) is making computer systems intelligent to do right thing. The AI is used today in a variety of fields, such as journalism, medical, industry as well as entertainment. The impact of AI is becoming larger day after day. In general, the AI system has to lead the optimal decision under uncertainty. But it is difficult for the AI system can derive the best conclusion. In addition, we have a trouble to represent the intelligent capacity of AI in numeric values. Statistics has the ability to quantify the uncertainty by two approaches of frequentist and Bayesian. So in this paper, we propose a methodology of the connection between statistics and AI efficiently. We compute a fixed value for estimating the population parameter using the frequentist learning. Also we find a probability distribution to estimate the parameter of conceptual population using Bayesian learning. To show how our proposed research could be applied to practical domain, we collect the patent big data related to Apple company, and we make the AI more intelligent to understand Apple's technology.

Fast Ambient Occlusion Volume Rendering using Local Statistics (지역적 통계량을 이용한 고속 환경-광 가림 볼륨 가시화)

  • Nam, Jinhyun;Kye, Heewon
    • Journal of Korea Multimedia Society
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    • v.18 no.2
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    • pp.158-167
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    • 2015
  • This study presents a new method to improve the speed of high quality volume rendering. We improve the speed of ambient occlusion which is one of the global illumination techniques used in traditional volume visualization. Calculating ambient occlusion takes much time because it determines an illumination value of a sample by integrating opacities of nearby samples. This study proposes an improved method for this by using local statistics such as averages and standard deviations. We calculate local statistics for each volume block, a set of nearby samples, in pre-processing time. In the rendering process, we efficiently determine the illumination value by assuming the density distribution as a normal distribution. As the results, we can generate high quality images that combine ambient occlusion illumination with local illumination in real time.

Image Segmentation Using Level Set Method with New Speed Function (새로운 속도함수를 갖는 레벨 셋 방법을 이용한 의료영상분할)

  • Kim, Sun-Worl;Cho, Wan-Hyun
    • The Korean Journal of Applied Statistics
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    • v.24 no.2
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    • pp.335-345
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    • 2011
  • In this paper, we propose a new hybrid speed function for image segmentation using level set. A new proposed speed function uses the region and boundary information of image object for the exact result of segmentation. The region information is defined by the probability information of pixel intensity in a ROI(region-of-interest), and the boundary information is defined by the gradient vector flow obtained from the gradient of image. We show the results of experiment for an various artificial image and real medical image to verify the accuracy of segmentation using proposed method.

Appearance-Order-Based Schema Matching

  • Ding, Guohui;Cao, Keyan;Wang, Guoren;Han, Dong
    • Journal of Computing Science and Engineering
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    • v.8 no.2
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    • pp.94-106
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    • 2014
  • Schema matching is widely used in many applications, such as data integration, ontology merging, data warehouse and dataspaces. In this paper, we propose a novel matching technique that is based on the order of attributes appearing in the schema structure of query results. The appearance order embodies the extent of the importance of an attribute for the user examining the query results. The core idea of our approach is to collect statistics about the appearance order of attributes from the query logs, to find correspondences between attributes in the schemas to be matched. As a first step, we employ a matrix to structure the statistics around the appearance order of attributes. Then, two scoring functions are considered to measure the similarity of the collected statistics. Finally, a traditional algorithm is employed to find the mapping with the highest score. Furthermore, our approach can be seen as a complementary member to the family of the existing matchers, and can also be combined with them to obtain more accurate results. We validate our approach with an experimental study, the results of which demonstrate that our approach is effective, and has good performance.

A Nonparametric Multivariate Test for a Monotone Trend among k Samples

  • Hyun, Noo-Rie;Song, Hae-Hiang
    • The Korean Journal of Applied Statistics
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    • v.22 no.5
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    • pp.1047-1057
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    • 2009
  • The nonparametric bivariate two-sample test of Bennett (1967) is extended to the multivariate k sample test. This test has been easily modified for a monotone trend among k samples. Often in applications it is important to consider a set of multivariate response variables simultaneously, rather than individually, and also important to consider testing k samples altogether. Different approaches of estimating the null covariance matrices of the test statistics resulted in the same limiting form. The multivariate k sample test is applied to the non-normal data of a randomized trial conducted for a period of four weeks in mental hospitals. The purpose of the trial is to compare the efficacy of three different interventions for a relief of the frequently occurring problems of constipation, caused as a side effect of antipsychotic drugs during hospitalization. The bowel movement status of patient for a week is summarized into a single severity score, and severity scores of four weeks comprise a four-dimensional multivariate variable. It is desirable with this trial data to consider a multivariate testing among k samples.

Association between Dietary Behavior and Esophageal Squamous Cell Carcinoma in Yanting

  • Zhao, Lin;Liu, Chun-Ling;Song, Qing-Kun;Deng, Ying-Mei;Qu, Chen-Xu;Li, Jun
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.20
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    • pp.8657-8660
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    • 2014
  • Background: Yanting is one of high risk areas for esophageal cancer and the screening program was therefore initiated there. This study was aimed to investigate the dietary behaviors on the risk of esophageal squamous cell carcinoma (ESCC), among the individuals with normal and abnormal esophagus mucosa. Materials and Methods: A frequency matched case-controls study was proposed to estimate the different distribution of dietary behavior between individuals of control, esophagitis and cancer groups. Cancer cases were selected from hospitals. Esophagitis cases and controls were selected from screening population for ESCC. Health workers collected data for 1 year prior to interview, in terms of length of finishing a meal, temperature of eaten food and interval between water boiling and drinking. Chi-square, Kruskal-Wallis tests and unconditional logistic regression model were used to estimate differences and associations between groups. Results: Compared with controls, length of finishing a meal ${\geq}15mins$ was related to a reduced OR for cancer (OR=0.46, 95%CI, 0.22-0.97) and even compared with cases of esophagitis, the OR of cancer was reduced to 0.30 (95%CI, 0.13-0.72). The OR for often eating food at a high temperature was 2.48 (95%CI 1.06, 5.82) for ESCC as compared with controls. Interval between water boiling and drinking of ${\geq}10mins$ was associated with lower risk of cancer: the OR was 0.18 compared with controls and 0.49 with esophagitis cases (p<0.05). Conclusions: Length of eating food ${\geq}15mins$ and interval between water boiling and drinking ${\geq}10mins$ are potentially related to reduced risk of esophageal SCC, compared with individuals with normal and abnormal esophageal mucosa. Recommendations to Yanting residents to change their dietary behaviors should be made in order to reduce cancer risk.

A Study on the agreement of Principal Diagnosis (주상병 일치도에 관한 연구 -1개 중소병원을 중심으로-)

  • Seo, Young-Suk;Kim, Yoo-Mi;Nam, Moon-Hee;Kang, Sung-Hong;Lim, Ji-Hye
    • Quality Improvement in Health Care
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    • v.15 no.1
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    • pp.123-133
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    • 2009
  • Background : The principal diagnosis has been used in many different fields such as hospital statistics, medical research, insurance claim, national health statistics and so on. Some principal diagnoses have a relatively low level of reliability in the medium-sized hospitals. The purpose of this study is to identify the reliability level of principal diagnoses and to suggest ways to improve reliability of the principal diagnosis. Method : Data were collected from a medium-sized hospital located in Pusan. The discharge summaries on 323 patients who were discharged in January, 2008 and the outpatient summaries on 251 patients who visited the hospital on March 28, 2008 were collected, and descriptive analysis was performed using SPSS version 12.0K. Result : The findings are the followings: (1) the diagnostic consistency rate between medical records and doctors' was 92.0%; (2) the diagnostic consistency rate between medical records and insurance claims was 86.1%; (3) the diagnostic consistency rate between doctors' diagnoses and insurance claims was 80.2%. The evidence seems to indicate that some principal diagnoses have reliability problems in the medium-sized hospitals. Conclusion : The results of this study suggest the followings: (1) employees should be trained and supervision of hospital activities are needed; (2) network systems should be constructed for each department; (3) professions need to be fostered (4) doctors' awareness of medical records should be changed.

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