• Korean Journal of Artificial Intelligence
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• v.8 no.2
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• pp.7-10
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• 2020

In this paper, a study was conducted to find main factorsto Pima Indians Diabetes based on machine learning. Diabetes is a type of metabolic disease such as insufficient secretion of insulin or inability to function normally and is characterized by a high blood glucose concentration. According to a situation report from WHO(World Health Organization), Diabetes is a chronic, metabolic disease characterized by elevated levels of blood glucose (or blood sugar), which leads over time to serious damage to the heart, blood vessels, eyes, kidneys and nerves. And also about 422 million people worldwide have diabetes, the majority living in low-and middle-income countries, and 1.6 million deaths are directly attributed to diabetes each year. Both the number of cases and the prevalence of diabetes have been steadily increasing over the past few decades. Therefore, in this study, we used Support Vector Machine (SVM), Decision Tree, and correlation analysisto discover three important factorsthat predict Pima Indians diabetes with 70% accuracy. Applying the results suggested in this paper, doctors can quickly diagnose potential Pima Indians diabetics and prevent Pima Indians diabetes.

• Proceedings of the KSEEG Conference
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• 2001.04a
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• pp.253-255
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• 2001

• Proceedings of the KSEEG Conference
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• 2002.04a
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• pp.341-343
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• 2002

• Korean Journal of Veterinary Research
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• v.63 no.2
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• pp.8.1-8.3
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• 2023

A 13-year-old neutered male Maltese dog presented to our hospital with lethargy and anorexia. Laboratory abnormalities included severe non-regenerative anemia (hematocrit, 12.9%; reticulocyte count 12.8 K/µL). The cytology of bone marrow revealed erythroid hypercellularity with mild myelofibrosis. Therefore, late-stage precursor-targeted immune-mediated anemia (PIMA) was diagnosed. Multimodal treatment including 2 immunosuppressant drugs (prednisolone and mycophenolate mofetil), antithrombic drug (clopidogrel), and blood transfusion was performed. The dog showed complete remission from PIMA, and the total duration of follow-up was 622 days. This is the first case report of canine PIMA managed successfully with prednisolone and mycophenolate mofetil in Korea.

• Proceedings of the KSEEG Conference
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• 2001.04a
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• pp.243-244
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• 2001

• Proceedings of the KSEEG Conference
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• 2001.04a
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• pp.245-246
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• 2001

• Proceedings of the KSEEG Conference
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• 2001.04a
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• pp.256-258
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• 2001

• Proceedings of the KSEEG Conference
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• 2002.04a
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• pp.338-340
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• 2002

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.775-791
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• 2017

We frequently encounter binary data in real life. Logistic, Probit, Cauchit, Complementary log-log models are often used for binary data analysis. In order to analyze binary data, Liu (2004) proposed a Robit model, in which the inverse of cdf of the Student's t distribution is used as a link function. Kim et al. (2008) also proposed a generalized t-link model to make the binary regression model more flexible. The more flexible skewed distributions allow more flexible link functions in generalized linear models. In the sense, we propose a binary data regression model using skewed generalized t distributions introduced in Theodossiou (1998). We implement R code of the proposed models using the glm function included in R base and R sgt package. We also analyze Pima Indian data using the proposed model in R.

• Journal of the Korea Society of Computer and Information
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• v.19 no.11
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• pp.149-157
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• 2014

Diabetes is a chronic disease that requires continuous medical care and patient-self management education to prevent acute complications and reduce the risk of long-term complications. The worldwide prevalence and incidence of diabetes mellitus are reached epidemic proportions in most populations. Early detection of diabetes could help to prevent its onset by taking appropriate preventive measures and managing lifestyle. The major objective of this research is to develop an automated decision support system for detection of diabetes using mixture of experts model. The performance of the classification algorithms was compared on the Pima Indians diabetes dataset. The result of this study demonstrated that the mixture of expert model achieved diagnostic accuracies were higher than the other automated diagnostic systems.