• The Korean Journal of Food & Health Convergence
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• v.8 no.6
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• pp.19-29
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• 2022

Business intelligence (BI) is a process for turning data into insights that inform an organization's strategic and tactical decisions. BI aims to give decision-makers the information they need to make better decisions Patient safety analysis, illness surveillance, and fraud identification are just a few healthcare decision-making processes that can be supported by data mining. Thus, the purpose of the current research is to outline the need if BI as an essential factor in the healthcare sector by reviewing various scholarly materials and the findings. The present author conducted one of the most famous qualitative literature approach which has been called as PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) statement. The selecting criteria for eligible prior studies were estimated by whether studies are suitable for the current research, identifying they are peer-reviewed and issued by notable publishers between 2017 and 2022. According to the result based on the PRISMA analysis, BI plays a vital role in the healthcare sector and there are four business intelligence factors (Data, Analytic, Reporting, and Visualization) that will ensure that the healthcare sector provides the right healthcare services to the customers to be addressed in this section include; data, analytics, reporting, and visualization.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.261-269
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• 2023

We propose to design a Holochain-based security and privacy protection system for resource-constrained IoT healthcare systems. Through analysis and performance evaluation, the proposed system confirmed that these characteristics operate effectively in the IoT healthcare environment. The system proposed in this paper consists of four main layers aimed at secure collection, transmission, storage, and processing of important medical data in IoT healthcare environments. The first PERCEPTION layer consists of various IoT devices, such as wearable devices, sensors, and other medical devices. These devices collect patient health data and pass it on to the network layer. The second network connectivity layer assigns an IP address to the collected data and ensures that the data is transmitted reliably over the network. Transmission takes place via standardized protocols, which ensures data reliability and availability. The third distributed cloud layer is a distributed data storage based on Holochain that stores important medical information collected from resource-limited IoT devices. This layer manages data integrity and access control, and allows users to share data securely. Finally, the fourth application layer provides useful information and services to end users, patients and healthcare professionals. The structuring and presentation of data and interaction between applications are managed at this layer. This structure aims to provide security, privacy, and resource efficiency suitable for IoT healthcare systems, in contrast to traditional centralized or blockchain-based systems. We design and propose a Holochain-based security and privacy protection system through a better IoT healthcare system.

• International journal of advanced smart convergence
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• v.6 no.2
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• pp.72-81
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• 2017

The developments in mobile technology and the increase in the production of smartphones have led to the growth of the mobile healthcare market. Moreover, the number of mobile healthcare apps is on the rise, and users are benefiting from using healthcare, exercise tracking, and body monitoring apps, as well as they have been searching for health information through mobile health apps. This paper evaluated the usability of a symptom checker application that provides information on diseases, treatment methods, and related hospitals through self-diagnosis of symptoms. Symptom checkers are currently being developed, and are widely used overseas. This paper sought to evaluate the usability of a symptom checker app, and suggested ways to introduce enhancements.

• International Journal of Knowledge Content Development & Technology
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• v.5 no.1
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• pp.49-68
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• 2015

Given a query (a health question), retrieval of relevant frequently asked questions (FAQs) is essential as the FAQs provide both reliable and readable information to healthcare consumers. The retrieval requires the estimation of the semantic similarity between the query and each FAQ. The similarity estimation is challenging as semantic structures of Chinese healthcare FAQs are quite different from those of the FAQs in other domains. In this paper, we propose a conceptual model for Chinese healthcare FAQs, and based on the conceptual model, present a technique ECA that estimates conceptual similarities between FAQs. Empirical evaluation shows that ECA can help various kinds of retrievers to rank relevant FAQs significantly higher. We also make ECA online to provide services for FAQ retrievers.

• International journal of advanced smart convergence
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• v.1 no.1
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• pp.27-33
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• 2012

In this paper, we analyze and simulate performance of space time block coded (STBC) binary pulse amplitude modulation-direct sequence (BPAM-DS) ultra-wideband (UWB) systems with double binary turbo code in indoor environments for various ubiquitous healthcare (u-healthcare) applications. Indoor wireless channel is modeled as a modified Saleh and Valenzuela (SV) model proposed as a UWB indoor channel model by the IEEE 802.15.SG3a in July 2003. In the STBC encoding process, an Alamouti algorithm for real-valued signals is employed because UWB signals have the type of real signal constellation. It is assumed that the transmitter has knowledge about channel state information. From simulation results, it is shown that the STBC scheme does not have an influence on improving bit error probability performance of the BPAM-DS UWB systems. It is also confirmed that the results of this paper can be applicable for u-healthcare applications.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.307-313
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• 2024

This study explores the integration of Explainable Artificial Intelligence (XAI) and network science in healthcare, focusing on enhancing healthcare data interpretation and improving diagnostic and treatment methods. Key methodologies like Graph Neural Networks, Community Detection, Overlapping Network Models, and Time-Series Network Analysis are examined in depth for their potential in patient health management. The research highlights the transformative role of XAI in making complex AI models transparent and interpretable, essential for accurate, data-driven decision-making in healthcare. Case studies demonstrate the practical application of these methodologies in predicting diseases, understanding drug interactions, and tracking patient health over time. The study concludes with the immense promise of these advancements in healthcare, despite existing challenges, and underscores the need for ongoing research to fully realize the potential of AI in this field.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.6
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• pp.2893-2900
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• 2014

Background: Statistical methods are very important to precisely measure breast cancer patient survival times for healthcare management. Previous studies considered basic statistics to measure survival times without incorporating statistical modeling strategies. The objective of this study was to develop a data-based statistical probability model from the female breast cancer patients' survival times by using the Bayesian approach to predict future inferences of survival times. Materials and Methods: A random sample of 500 female patients was selected from the Surveillance Epidemiology and End Results cancer registry database. For goodness of fit, the standard model building criteria were used. The Bayesian approach is used to obtain the predictive survival times from the data-based Exponentiated Exponential Model. Markov Chain Monte Carlo method was used to obtain the summary results for predictive inference. Results: The highest number of female breast cancer patients was found in California and the lowest in New Mexico. The majority of them were married. The mean (SD) age at diagnosis (in years) was 60.92 (14.92). The mean (SD) survival time (in months) for female patients was 90.33 (83.10). The Exponentiated Exponential Model found better fits for the female survival times compared to the Exponentiated Weibull Model. The Bayesian method is used to obtain predictive inference for future survival times. Conclusions: The findings with the proposed modeling strategy will assist healthcare researchers and providers to precisely predict future survival estimates as the recent growing challenges of analyzing healthcare data have created new demand for model-based survival estimates. The application of Bayesian will produce precise estimates of future survival times.

• The Korea Journal of Herbology
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• v.33 no.5
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• pp.39-46
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• 2018

Objectives : This study was aimed to assess the current educational environment of herbology and the possibility of collaborative learning of herbology with another discipline. This study will present information that can be used to find the direction of further researches and can be applied to the education of herbology. Methods : An online questionnaire was developed with and sent through SurveyMonkey to 242 korean medicine college students in Korea. The questionnaire comprised questions pertaining to herbology education in Korean Medicine universities and international healthcare cooperation education. The validity and reliability of the questionnaire were evaluated, and Spearman's correlation coefficients for two types of questions were evaluated. Results : Among the questions about herbology education, those regarding the necessity of learning clinical cases using herbal medicines for preventing infectious diseases were scored the highest. Students were mostly interested in the effects and indications of herbal drugs. Even students answered they did not learn about official development assistance, 79.85% students answered that they were interested in careers related with the international cooperation or willing to participate in the international cooperation. Three types of correlations showed a statistically significant correlation. Conclusions : This study suggests that herbology education about its effects and indications needs further improvement for competency-based education. Furthermore, herbology can play a critical role in competency-based education for Korean medicine students if a well-designed career program is developed for them.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.4
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• pp.1105-1109
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• 2012

Breast cancer is the second most common cancer in women in India and the disease burden is increasing annually. The lack of awareness initiatives, structured screening, and affordable treatment facilities continue to result in poor survival. We present a breast cancer survival scenario, in urban population in India, where standardised care is distributed equitably and free of charge through an employees' healthcare scheme. We studied 99 patients who were treated at our hospital during the period 2005 to 2010 and our follow-up rates were 95.95%. Patients received evidence-based standardised care in line with the tertiary cancer centre in Mumbai. One-, three- and five-year survival rates were calculated using Kaplan-Meier method. Socio-demographic, reproductive and tumor factors, relevant to survival, were analysed. Mortality hazard ratios (HR) were calculated using Cox proportional hazard method. Survival in this series was compared to that in registries across India and discrepancies were discussed. Patients mean age was 56 years, mean tumor size was 3.2 cms, 85% of the tumors belonged to T1 and T2 stages, and 45% of the patients belonged to the composite stages I and IIA. Overall 5-year survival was 74.9%. Patients who presented with large-sized tumors (HR 3.06; 95% CI 0.4-9.0), higher composite stage (HR 1.91; 0.55-6.58) and undergone mastectomy (HR 2.94; 0.63-13.62) had a higher risk of mortality than women who had higher levels of education (HR 0.25; 0.05-1.16), although none of these results reached the significant statistical level. We observed 25% better survival compared to other Indian populations. Our results are comparable to those from the European Union and North America, owing to early presentation, equitable access to standardised free healthcare and complete follow-up ensured under the scheme. This emphasises that equitable and affordable delivery of standardised healthcare can translate into early presentation and better survival in India.

• Health Policy and Management
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• v.33 no.2
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• pp.157-165
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• 2023

Background: We aimed to provide basic data for improving the effectiveness of the invitational training and reflecting it in the program in the following year by identifying the satisfaction level of trainees who participated in the "Dr. LEE Jong-wook Fellowship Program" funded by the Korea Foundation for International Healthcare. Methods: A qualitative study was conducted using a questionnaire interview. In the first stage of analysis, only the interview contents related to the research topic were classified by the researcher for the conversations recorded at the interview site, and in the second stage of analysis, the interview contents classified in the first stage were classified into each of those mentioned in this study. Results: The longer the trainees participated in the program and the better the accessibility, the higher the satisfaction with the program. In addition, the level of achievement of the trainees' goals and the level of improvement in their competence affected their satisfaction, and their difficulty in language communication during the training period was identified as a factor affecting the trainees' satisfaction level. In addition, competency improvement and satisfaction were positively correlated (r=0.75, p=0.03). Conclusion: When organizing a rehabilitation workforce capacity training program, it is important to identify trainees' needs, ensure accessibility, organize courses effectively, enhance English proficiency, and expand practical lectures to increase trainees' knowledge and understanding of rehabilitation.