• Management & Information Systems Review
• /
• v.32 no.5
• /
• pp.19-43
• /
• 2013

The diffusion of new technology has traditionally focused on the adoption perspective. Researchers refer this use-diffusion paradigm to behaviors of use after adoption. This study intends to analyse the influential factors of use-diffusion and continual use of website and applications in medical service. To achieve this a use-diffusion model as a conceptual frame work is suggested. Medical information quality, personal innovativeness and subjective norm are assumed as antecedent variables medical website and application's rate of use, variety of use, and continued use intention as result variables. According to the empirical study results medical information quality, web based application usability, personal innovativeness, and subjective norm have a meaningful influence on medical service consumer's use-diffusion patterns. Also pattern of use influences the continued use intention. This study provides an opportunity to understand medical service consumer's behavior after website and application use adoption and suggests further directions for establishing medical service online marketing strategy by determining influential factors of use-diffusion and continued use of medical online marketing tools.

• Korean Journal of Radiology
• /
• v.24 no.2
• /
• pp.155-165
• /
• 2023

Objective: Little is known about the effects of using different expert-determined reference standards when evaluating the performance of deep learning-based automatic detection (DLAD) models and their added value to radiologists. We assessed the concordance of expert-determined standards with a clinical gold standard (herein, pathological confirmation) and the effects of different expert-determined reference standards on the estimates of radiologists' diagnostic performance to detect malignant pulmonary nodules on chest radiographs with and without the assistance of a DLAD model. Materials and Methods: This study included chest radiographs from 50 patients with pathologically proven lung cancer and 50 controls. Five expert-determined standards were constructed using the interpretations of 10 experts: individual judgment by the most experienced expert, majority vote, consensus judgments of two and three experts, and a latent class analysis (LCA) model. In separate reader tests, additional 10 radiologists independently interpreted the radiographs and then assisted with the DLAD model. Their diagnostic performance was estimated using the clinical gold standard and various expert-determined standards as the reference standard, and the results were compared using the t test with Bonferroni correction. Results: The LCA model (sensitivity, 72.6%; specificity, 100%) was most similar to the clinical gold standard. When expert-determined standards were used, the sensitivities of radiologists and DLAD model alone were overestimated, and their specificities were underestimated (all p-values < 0.05). DLAD assistance diminished the overestimation of sensitivity but exaggerated the underestimation of specificity (all p-values < 0.001). The DLAD model improved sensitivity and specificity to a greater extent when using the clinical gold standard than when using the expert-determined standards (all p-values < 0.001), except for sensitivity with the LCA model (p = 0.094). Conclusion: The LCA model was most similar to the clinical gold standard for malignant pulmonary nodule detection on chest radiographs. Expert-determined standards caused bias in measuring the diagnostic performance of the artificial intelligence model.

• International Journal of Quality Innovation
• /
• v.10 no.2
• /
• pp.109-126
• /
• 2009

The purpose of this study was to examine overall customer satisfaction associated with medical service quality in Taiwan by integrated Kano's model and customer satisfaction index model. Another purpose was to confirmed nonlinear and asymmetric relationship of Customer Satisfaction and Quality Performance by the research outcome. By analyzing 1,100 patients or their family members, this study used the structural equation model (SEM) with AMOS software for data analysis. The results show that must-be attributes, one-dimensional attributes and attractive attributes had a direct effect on overall customer satisfaction, Surprisingly, overall customer satisfaction had positively influenced customer loyalty customer satisfaction had negatively influenced customer complaints. The study also found that customer complaints have direct effect on customer loyalty. Importantly, the study found out the must-be attributes, the attractive attributes and one-dimensional attributes increased, the level of overall customer satisfaction also increased. The customer satisfaction positively influences customer loyalty in medical service quality in Taiwan. The findings might reveal new insights for researchers dealing with quality of medical service and for hospital managers who devote resources exclusively to achieving highest possible levels of patient satisfaction.

• Journal of KIISE
• /
• v.42 no.12
• /
• pp.1590-1599
• /
• 2015

As a variety of personal medical devices appear, it is possible to acquire a large number of diverse medical contexts from the devices. There have been efforts to analyze the medical contexts via software applications. In this paper, we propose a generic model of medical analytics schemes that are used by medical experts, identify inference methods for realizing each medical analytics scheme, and present guidelines for applying the inference methods to the medical analytics schemes. Additionally, we develop a PoC inference system and analyze real medical contexts to diagnose relevant diseases so that we can validate the feasibility and effectiveness of the proposed medical analytics schemes and guidelines of applying inference methods.

• The Journal of Industrial Distribution & Business
• /
• v.15 no.5
• /
• pp.17-27
• /
• 2024

Purpose: The renminbi (RMB) has appreciated alongside the elevation of China's economic status, leading to increased exchange rate volatility. Moreover, China's medical industry saw a surge in import and export trade volume, with trade related to epidemic prevention and control in the medical sector significantly increasing its share. The medical device trade, in particular, occupies a substantial portion of this trade. Research design, data and methodology: This paper focuses on the import and export value of medical devices in the medical industry as a case study to explore the impact of RMB exchange rate fluctuations on the import and export trade of the medical industry during the pandemic. Additionally, it investigates whether the import and export trade of the medical industry can be a contributing factor to the fluctuations in the RMB exchange rate. Results: Through an empirical study on the import and export values of medical devices in the medical industry over the past three years, as well as the RMB exchange rate, this paper establishes a VAR model and conducts a series of tests including stationarity tests and cointegration tests. Conclusions: The conclusion is that fluctuations in the RMB exchange rate have a long-term impact on China's medical industry's import and export trade.

• 대한예방의학회:학술대회논문집
• /
• 1994.02b
• /
• pp.150-153
• /
• 1994

Receiver operating characteristic (ROC) curves have been frequently used to compare probability models applied to medical problems. Though the curves are a measure of the discriminatory power of a model. they do not reflect the model's accuracy. A supplementary accuracy curve is derived which will be coincident with the ROC curve if the model is reliable. will be above the ROC curve if the model's probabilities are too high or below if they are too low. A clinical example of this new graphical presentation is given.

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

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.9
• /
• pp.157-164
• /
• 2012

Recently medical service environment, the clinical information exchange which contribute to medical safety, promotion of service quality and patient's convenience, efficiency of medical procedures and medical management is essential medical service model. But, practical exchange of clinical information which variation of information level, absence of standardization system, build of heterogeneous information systems is difficult in each medical institute. In this paper, We analyzed the related technical standardizations and the models of clinical information exchange. So, we designed the clinical information exchange system based on the ideal lazy response model which is aimed at vitalizations the exchange of clinical information under domestic law environment. In case of exchange the clinical information, we separate CDA document flow from metadata flow. As a experimental result we acquired 24% improved performance compared with existed system based on the lazy response model.

• The KIPS Transactions:PartC
• /
• v.18C no.6
• /
• pp.379-388
• /
• 2011

Ensuring the security of medical records is becoming an increasingly important problem as modern technology is integrated into existing medical services. As a consequence of the adoption of EMR(Electronic Medical Records) in the health care sector, it is becoming more and more common for a health professional to edit and view a patient's record. In order to protect the patient's privacy, a secure authentication model to access the electronic medical records system must be used. A traditional identity based digital certificate for the authenticity of EMR has private key management and key escrow of a user's private key. In order to protect the EMR, The traditional authentication system is based on the digital certificate. The identity based digital certificate has many disadvantages, for example, the private key can be forgotten or stolen, and can be easily escrow of the private key. Nowadays, authentication model using fingerprint recognition technology for EMR has become more prevalent because of the advantages over digital certificate -based authentication model. Because identity-based fingerprint recognition can eliminate disadvantages of identity-based digital certificate, the proposed authentication model provide high security for access control in EMR.

• Journal of Preventive Medicine and Public Health
• /
• v.57 no.2
• /
• pp.167-175
• /
• 2024

Objectives: Rural housewives are integral to household management and family care, yet their sedentary lifestyles present significant health risks. This study used the transtheoretical model (TTM) to investigate strategies that encourage and maintain regular exercise habits among rural housewives. Methods: A semi-experimental study was conducted in 2021 with 114 housewives aged 30 to 59 who attended rural health centers in Gorgan, Iran. Participants were randomly assigned to 1 of 2 groups. Data collection involved a validated questionnaire that gathered demographic information and constructs of the TTM. The intervention group participated in a comprehensive educational program, which included four 60-minute sessions. Data were collected again 6 months post-intervention and analyzed using descriptive and inferential statistics in SPSS version 21. Results: The study encompassed women with an average age of 39.75±6.05 years, the majority of whom had educational levels below a diploma, and over 90% were married. We observed strong correlations between the processes of change, self-efficacy, and decisional balance. At the outset, there were no significant differences in demographics or model structures between the 2 groups. However, 6 months post-intervention, the intervention group exhibited statistically significant differences in the mean scores of model structures, stages of change, and body mass index (p<0.05). Conclusions: This study highlights the importance of physical activity training for rural housewives. The findings suggest that the educational intervention, which utilized the TTM, significantly impacted the participants' model structures and their stages of change.