• Asian Pacific Journal of Cancer Prevention
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• v.15 no.1
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• pp.3-10
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• 2014

The Japan National Committee for the Union for International Cancer Control (UICC) and UICC-Asia Regional Office (ARO) organized an international session as part of the official program of the 72nd Annual Meeting of the Japanese Cancer Association to discuss the topic "What is cost-effectiveness in cancer treatment?" Healthcare economics are an international concern and a key issue for the UICC. The presenters and participants discussed the question of how limited medical resources can be best used to support life, which is a question that applies to both developing and industrialized countries, given that cancer treatment is putting medical systems under increasing strain. The emergence of advanced yet hugely expensive drugs has prompted discussion on methodologies for Health Technology Assessment (HTA) that seek to quantify cost and effect. The session benefited from the participation of various stakeholders, including representatives of industry, government and academia and three speakers from the Republic of Korea, an Asian country where discussion on HTA methodologies is already advanced. In addition, the session was joined by a representative of National Institute for Health and Care Excellence (NICE) of the United Kingdom, which has pioneered the concept of cost-effectiveness in a medical context. The aim of the session was to advance and deepen understanding of the issue of cost-effectiveness as viewed from medical care systems in different regions.

• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.262-269
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• 2017

The purpose of this study is to provide direction of medical education by analysing medical school student's perception structure about 'happy doctor'. In particular, this study compared perception structure between two groups of students before clerkship and after clerkship. The subject of this study were 1~4 academic year students in medical school. Students' text about 'happy doctor' were collected by open-ended questionnaire and analyzed by using sematic network analysis. Based on the result of network analysis, perception structure of each groups were confirmed. The network of each groups have 'Professionalism' group including words such as 'patient', 'treatment', 'worthwhile' in common. Three groups, 'Professionalism', 'Quality of life' and 'Self-realization' constituted the before clerkship network. And five groups, 'Professionalism', 'Time with family', 'Balance between work and household', 'Interpersonal relationship', 'Physical and psychological health' constituted the after clerkship network. The results of this study is expected to contribute for developing the basic medical education curriculum for 'happy doctor'.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.150-156
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• 2023

For a doctor, diagnosing a patient's heart disease is not easy. It takes the ability and experience with high flying hours to be able to accurately diagnose the type of patient's heart disease based on the existing factors in the patient. Several studies have been carried out to develop tools to identify types of heart disease in patients. However, most only focus on the results of patient answers and lab results, the rest use only echocardiography data or electrocardiogram results. This research was conducted to test how accurate the results of the classification of heart disease by using two medical data, namely echocardiography and electrocardiogram. Three treatments were applied to the two medical data and analyzed using the decision tree approach. The first treatment was to build a classification model for types of heart disease based on echocardiography and electrocardiogram data, the second treatment only used echocardiography data and the third treatment only used electrocardiogram data. The results showed that the classification of types of heart disease in the first treatment had a higher level of accuracy than the second and third treatments. The accuracy level for the first, second and third treatment were 78.95%, 73.69% and 50%, respectively. This shows that in order to diagnose the type of patient's heart disease, it is advisable to look at the records of both the patient's medical data (echocardiography and electrocardiogram) to get an accurate level of diagnosis results that can be accounted for.

• Radiation Oncology Journal
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• v.37 no.1
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• pp.13-21
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• 2019

Purpose: Glioblastoma (GBM) carries a high propensity for in-field failure despite trimodality management. Past studies have failed to show outcome improvements with dose-escalation. Herein, we examined trends and outcomes associated with dose-escalation for GBM. Materials and Methods: The National Cancer Database was queried for GBM patients who underwent surgical resection and external-beam radiation with chemotherapy. Patients were excluded if doses were less than 59.4 Gy; dose-escalation referred to doses ≥66 Gy. Odds ratios identified predictors of dose-escalation. Univariable and multivariable Cox regressions determined potential predictors of overall survival (OS). Propensity-adjusted multivariable analysis better accounted for indication biases. Results: Of 33,991 patients, 1,223 patients received dose-escalation. Median dose in the escalation group was 70 Gy (range, 66 to 89.4 Gy). The use of dose-escalation decreased from 8% in 2004 to 2% in 2014. Predictors of escalated dose were African American race, lower comorbidity score, treatment at community centers, decreased income, and more remote treatment year. Median OS was 16.2 months and 15.8 months for the standard and dose-escalated cohorts, respectively (p = 0.35). On multivariable analysis, age >60 years, higher comorbidity score, treatment at community centers, decreased education, lower income, government insurance, Caucasian race, male gender, and more remote year of treatment predicted for worse OS. On propensity-adjusted multivariable analysis, age >60 years, distance from center >12 miles, decreased education, government insurance, and male gender predicted for worse outcome. Conclusion: Dose-escalated radiotherapy for GBM has decreased over time across the United States, in concordance with guidelines and the available evidence. Similarly, this large study did not discern survival improvements with dose-escalation.

• Journal of information and communication convergence engineering
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• v.8 no.5
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• pp.586-590
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• 2010

Medical technology is gradually being developed by applying information technologies. Especially, RFID technology is being used for precise disease history information of patients [4]. And in case the patient is far away, the patient can be treated using network communication of the internet [5][6]. The internet makes us to treat or operate the patient without being restricted to time or space. If the above technologies are made as a system, the patient can be treated or operated without being restricted to time or space. In this paper, we present a patient treatment system has been implemented with a system using RFID and network communication of the internet [1][2][3][4]. The system is driven as follows. First, the information of patient can be checked from a remote PC, if the tag that a patient has been read through a reader. And a remote treatment is performed by controlling robot's arm with a joystick using internet network [19][20][21]. The RFID system was implemented in frequency of 125 KHz [1]. The information of patient can be checked with PDA, PC and C-LCD using Bluetooth and WLAN [7][8][9][10]. For the treatment and operation of the patient, the robot's arm has been formed using AX-12 motor, joystick and two buttons [11][12][13][14][15] [17][18].

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.631-638
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• 2015

The purpose of this study is to provide developmental direction of medical education by analysing graduate medical school student's perception structure about 'good doctor' and the difference between graduate medical school student's perception structure about 'good doctor' before and after clerkship. Subject of study is medical students in 1st~4th year. NetMiner 4.0 program, which is social network analysis, was used to analyse. Many of the words that students used to describe good doctor were similar. But especially lots of times they used 'patient', 'treatment', 'competence', 'heart' and a word 'patient' showed highest degree centrality. Higher density of network and mean degree centrality were shown in students who experienced clerkship. 'Diagnosis and treatment', 'medical communication', 'attitudes to patients', 'medical knowledge', 'basic competence' these 5 groups were shown in network of students before and after clerkship in common. In the case of students after clerkship, 'lifelong learning ' groups have been added, so were the 6 groups. Considering the fact that social responsibility, professionalism, medical humanities are emphasized in recent medical education, students have lack of perception structure about good doctor, therefore education of this area needs to be strengthened.

• IMMUNE NETWORK
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• v.22 no.1
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• pp.12.1-12.13
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• 2022

Allergen-specific immunotherapy (AIT) is presumed to modulate the natural course of allergic disease by inducing immune tolerance. However, conventional AITs, such as subcutaneous immunotherapy and sublingual immunotherapy, require long treatment durations and often provoke local or systemic hypersensitivity reactions. Therefore, only <5% of allergy patients receive AIT as second-line therapy. Novel administration routes, such as intralymphatic, intradermal and epicutaneous immunotherapies, and synthetic recombinant allergen preparations have been evaluated to overcome these limitations. We will review the updated views of diverse AIT methods, and discuss the limitations and opportunities of the AITs for the treatment of allergic diseases in humans.

• The Korean Journal of Physiology and Pharmacology
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• v.28 no.5
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• pp.479-491
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• 2024

Improving liver regeneration (LR) remains a medical issue, and there is currently a lack of safe and effective drugs for LR. Rhizoma Dioscoreae (SanYak, SY) is a traditional Chinese medicine. However, the underlying action mechanism of SY treatment for LR is yet to be fully elucidated. To explore the mechanism by which SY affects LR, we have conducted a series of methods for network pharmacological analysis, molecular docking, and in vivo experimental validation in mice. Overall, 9 compounds and 30 predicted target genes of SY were found to be associated with the therapeutic effects of LR. Compared with the model group, hematoxylin and eosin staining revealed that the mice with preoperative drug intervention possessed fewer postoperative hepatocyte bubbles and relatively regular morphology. Furthermore, the serum alanine transaminase and aspartate aminotransferase levels were reduced, immunohistochemistry revealed elevated proliferating cell nuclear antigen positivity rate, and Western blotting demonstrated that the phospho-protein kinase B (AKT)/AKT ratio was downregulated and that vascular endothelial growth factor A (VEGFA) expression levels were upregulated. This study explored dioscin, the main active ingredient of SY, and its potential therapeutic effects on LR. It repairs damaged liver following surgery and promotes liver cell proliferation. The action mechanism comprises reducing AKT phosphorylation levels and upregulating VEGFA expression levels. Thus, this study provides a new direction for further research on the mechanism of SY promoting LR.

• The Korean Journal of Physiology and Pharmacology
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• v.18 no.2
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• pp.177-182
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• 2014

This study was to determine the correlation between endothelial function and neuro-endocrine-immune (NEI) network through observing the changes of NEI network under the different endothelial dysfunction models. Three endothelial dysfunction models were established in male Wistar rats after exposure to homocysteine (Hcy), high fat diet (HFD) and Hcy+HFD. The results showed that there was endothelial dysfunction in all three models with varying degrees. However, the expression of NEI network was totally different. Interestingly, treatment with simvastatin was able to improve vascular endothelial function and restored the imbalance of the NEI network, observed in the Hcy+HFD group. The results indicated that NEI network may have a strong association with endothelial function, and this relationship can be used to distinguish different risk factors and evaluate drug effects.

• Journal of Biomedical Engineering Research
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• v.38 no.5
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• pp.237-241
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• 2017

Early detection of the pulmonary nodule is important for diagnosis and treatment of lung cancer. Recently, CT has been used as a screening tool for lung nodule detection. And, it has been reported that computer aided detection(CAD) systems can improve the accuracy of the radiologist in detection nodules on CT scan. The previous study has been proposed a method using Convolutional Neural Network(CNN) in Lung CAD system. But the proposed model has a limitation in accuracy due to its sparse layer structure. Therefore, we propose a Deep Convolutional Neural Network to overcome this limitation. The model proposed in this work is consist of 14 layers including 8 convolutional layers and 4 fully connected layers. The CNN model is trained and tested with 61,404 regions-of-interest (ROIs) patches of lung image including 39,760 nodules and 21,644 non-nodules extracted from the Lung Image Database Consortium(LIDC) dataset. We could obtain the classification accuracy of 91.79% with the CNN model presented in this work. To prevent overfitting, we trained the model with Augmented Dataset and regularization term in the cost function. With L1, L2 regularization at Training process, we obtained 92.39%, 92.52% of accuracy respectively. And we obtained 93.52% with data augmentation. In conclusion, we could obtain the accuracy of 93.75% with L2 Regularization and Data Augmentation.