• Korea Journal of Hospital Management
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• v.12 no.4
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• pp.1-21
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• 2007

The relaxation of the regulation in selection of medical institution allows patients to use their own judgement in choosing proper institution for their diseases. Since the change of the regulation, there should have been many changes in medical institution selection behavior. The analysis of the change in disease specific selection pattern is critical because there be an optimal selection criteria that ensure the efficient and effective utilization of medical resources. This study analysis the institution selection factors by comparing the choice among the cases of acute diseases, the cases of chronic diseases, inpatient services, outpatient services, and emergency medical service. The comparisons performed in terms of size, class and other characteristics of medical institutions. For the study the nationally surveyed database was used and the data were analyzed using logistic regression procedure. The results indicates that the primary care facilities were not properly utilized. This study speculates that the reason for the undesirable pattern of utilization is that the roles of primary care facilities in the healthcare delivery system was not clearly defined. Based on the results, the medical policy implications are discussed.

• Journal of Physiology & Pathology in Korean Medicine
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• v.35 no.5
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• pp.132-138
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• 2021

Artificial intelligence technology sheds light on new ways of innovating acupuncture research. As acupoint selection is specific to target diseases, each acupoint is generally believed to have a specific indication. However, the specificity of acupoint selection may be not always same with the specificity of acupoint indication. In this review, we propose that the specificity of acupoint indication can be inferred from clinical data using reverse inference. Using forward inference, the prescribed acupoints for each disease can be quantified for the specificity of acupoint selection. Using reverse inference, targeted diseases for each acupoint can be quantified for the specificity of acupoint indication. It is noteworthy that the selection of an acupoint for a particular disease does not imply the acupoint has specific indications for that disease. Electronic medical record includes various symptoms and chosen acupoint combinations. Data mining approach can be useful to reveal the complex relationships between diseases and acupoints from clinical data. Combining the clinical information and the bodily sensation map, the spatial patterns of acupoint indication can be further estimated. Interoperable medical data should be collected for medical knowledge discovery and clinical decision support system. In the era of artificial intelligence, machine learning can reveal the associations between diseases and prescribed acupoints from large scale clinical data warehouse.

• Korean Journal of Acupuncture
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• v.31 no.3
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• pp.108-116
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• 2014

Objectives : The purpose of this study is to identify changes of texts by investigating similarities and differences of the third chapter of limb diseases section between Beijiqianjinyaofang(BJQJYF) and Sunzhenrenqianjinfang(SZRQJF). Methods : I reviewed the third chapter of limb diseases section both of BJQJYF and SZRQJF and analysed the changes of texts. Results : 1. Hand, shoulder and low back pains mentioned in the second chapter of glossopathy from SZRQJF were moved to the third chapter of limb diseases in BJQJYF. 2. Inappropriate indications were changed reasonably. 3. Contents related with treatment were revised, by addition or deletion of contents. 4. There were some contents which were worth clinically in SZRQJF. 5. The rule of choosing acupoints for hand, arm, leg, knee and limb disease was selection of local points, and for shoulder and low back disease was selection of distant points. Conclusions : Classification and contents of the third chapter of limb diseases were re-organized systematically through proofreading by medical printing authority. However, some contents deleted from SZRQJF were worth clinically, and more studies are necessary to identify the reason why the indication and selection of acupoints were changed by proofreading.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.177-184
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• 2021

All over the world, people are affected by many chronic diseases and medical practitioners are working hard to find out the symptoms and remedies for the diseases. Many researchers focus on the feature detection of the disease and trying to get a better health recommendation system. It is necessary to detect the features automatically to provide the most relevant solution for the disease. This research gives the framework of Health Recommendation System (HRS) for identification of relevant and non-redundant features in the dataset for prediction and recommendation of diseases. This system consists of three phases such as Pre-processing, Feature Selection and Performance evaluation. It supports for handling of missing and noisy data using the proposed Imputation of missing data and noise detection based Pre-processing algorithm (IMDNDP). The selection of features from the pre-processed dataset is performed by proposed ensemble-based feature selection using an expert's knowledge (EFS-EK). It is very difficult to detect and monitor the diseases manually and also needs the expertise in the field so that process becomes time consuming. Finally, the prediction and recommendation can be done using Support Vector Machine (SVM) and rule-based approaches.

• Korean Journal of Acupuncture
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• v.37 no.3
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• pp.203-208
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• 2020

Objectives : Since there are complex associations between diseases/symptoms and acupoints, one-to-one correspondence may not be the proper approach. Pattern identification has been being used as a clinical framework to make treatment decisions by extracting and synthesizing clinical data including patients' signs and symptoms. In this article, we propose two different models explaining the relationships between diseases and acupoints based on the branch treatment [Zhibiaofa] and the root treatment [Zhibenfa]. Methods : We explained the relationships between diseases/symptoms and acupoints from the example data from our previous study on traditional acupuncture point selection patterns for pain control. Diseases include low back pain, migraine, irritable bowel syndrome, osteoarthritis, ankle sprain, carpal tunnel syndrome, and dysmenorrhea, and acupoints included LI4, BL23, BL25, SP6, BL60, TE5, and CV4. Results : The relationships between diseases/symptoms and acupoints can be explained directly based on the branch treatment, and also can be explained indirectly through pattern identification based on the root treatment. Pattern identifications included both meridian-based pattern identification based on the spatial information of diseases and visceral organ-based pattern identification based on the characteristics of diseases. Conclusions : In the East Asian traditional medicine, Korean medicine doctors choose the most appropriate acupoints based either on the diseases/symptoms (i.e., branch treatment) or on the results of pattern identifications (i.e., root treatment). It is necessary to understand the two different approaches to choose specific acupoints for the targeted diseases.

• Parasites, Hosts and Diseases
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• v.55 no.5
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• pp.473-480
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• 2017

Plasmodium vivax merozoite surface protein-1 (PvMSP1) gene codes for a major malaria vaccine candidate antigen. However, its polymorphic nature represents an obstacle to the design of a protective vaccine. In this study, we analyzed the genetic polymorphism and natural selection of the C-terminal 42 kDa fragment within PvMSP1 gene ($PvMSP1_{42}$) from 77 P. vivax isolates, collected from imported cases of China-Myanmar border (CMB) areas in Yunnan province and the inland cases from Anhui, Yunnan, and Zhejiang province in China during 2009-2012. Totally, 41 haplotypes were identified and 30 of them were new haplotypes. The differences between the rates of non-synonymous and synonymous mutations suggest that $PvMSP1_{42}$ has evolved under natural selection, and a high selective pressure preferentially acted on regions identified of $PvMSP1_{33}$. Our results also demonstrated that $PvMSP1_{42}$ of P. vivax isolates collected on China-Myanmar border areas display higher genetic polymorphisms than those collected from inland of China. Such results have significant implications for understanding the dynamic of the P. vivax population and may be useful information towards China malaria elimination campaign strategies.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.339-345
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• 2022

Cardiovascular diseases is one of the leading causes of death in the world. The objectives of this study were to build various models using sociodemographic variables based on three variable selection methods and seven machine learning algorithms for the identification of hypertension and dyslipidemia and to evaluate predictive powers of the models. In experiments based on full variables and correlation-based feature subset selection methods, our results showed that performance of models using naive Bayes was better than those of models using other machine learning algorithms in both two diseases. In wrapper-based feature subset selection method, performance of models using logistic regression was higher than those of models using other algorithms. Our finding may provide basic data for public health and machine learning fields.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.435-446
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• 2020

With the ability to learn rules from training data, the machine learning model can classify unknown objects. At the same time, the dimension of hyperspectral data is usually large, which may cause an over-fitting problem. In this research, an identification methodology of tea diseases was proposed based on spectral reflectance and machine learning, including the feature selector based on the decision tree and the tea disease recognizer based on random forest. The proposed identification methodology was evaluated through experiments. The experimental results showed that the recall rate and the F1 score were significantly improved by the proposed methodology in the identification accuracy of tea disease, with average values of 15%, 7%, and 11%, respectively. Therefore, the proposed identification methodology could make relatively better feature selection and learn from high dimensional data so as to achieve the non-destructive and efficient identification of different tea diseases. This research provides a new idea for the feature selection of high dimensional data and the non-destructive identification of crop diseases.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.2910-2925
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• 2017

Inadequate and inappropriate intake of food is known to cause various health issues and diseases. Due to lack of concise information about healthy diet, people have to rely on medicines instead of taking preventive measures in food intake. Due to diversity in food components and large number of dietary sources, it is challenging to perform real-time selection of diet patterns that must fulfill one's nutrition needs. Particularly, selection of proper diet is critical for patients suffering from various diseases. In this article, we highlight the issue of selection of proper diet that must fulfill patients' nutrition requirements. To address this issue, we present a cloud based food recommendation system, called Diet-Right, for dietary recommendations based on users' pathological reports. The model uses ant colony algorithm to generate optimal food list and recommends suitable foods according to the values of pathological reports. Diet-Right can play a vital role in controlling various diseases. The experimental results show that compared to single node execution, the convergence time of parallel execution on cloud is approximately 12 times lower. Moreover, adequate accuracy is attainable by increasing the number of ants.

• The Korean Journal of Health Service Management
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• v.3 no.1
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• pp.47-58
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• 2009

This study is to grasp selection factors and habits of information searching of customers of ophthalmic service and to verify the differences in them and to investigate how they affect in selecting medical institute by demographic sociological characters, selection factors by classification and habits of information searching, how many times they used and the type of medical treatment. The result of analysis of importance of selection factors of medical institute, it showed that doctors' career were evaluated high by classification and it showed in order of university hospital, hospital, clinic in facilities and equipment and in order of university hospital, clinic, hospital in distance transportation Analysis of importance of selection factors by sex distinction, it showed that doctors' career were high for both male and female and according to the result of analysis of selection factors by an age, doctors' career variable was measured high and it showed in order of facilities, equipment, distance and convenient transportation. The result of analysis by the form of medical treatment, doctors' career were measured high in all diseases. Facilities and equipment were measured high in case of a corrective operation of eyesight and distance transportation variable showed high in simple eye diseases. According to the result of analysis of habits of searching information by utility frequency, one's own experience in the past(direct visits) was the highest over all and it showed in order of introduction of other ophthalmic department in case of people who go to the institutes many times.