• Communications of Mathematical Education
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• v.34 no.1
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• pp.1-15
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• 2020

Today's healthcare, intelligent robots, smart home systems, and car sharing are already innovating with cutting-edge information and communication technologies such as Artificial Intelligence (AI), the Internet of Things, the Internet of Intelligent Things, and Big data. It is deeply affecting our lives. In the factory, robots have been working for humans more than several decades (FA, OA), AI doctors are also working in hospitals (Dr. Watson), AI speakers (Giga Genie) and AI assistants (Siri, Bixby, Google Assistant) are working to improve Natural Language Process. Now, in order to understand AI, knowledge of mathematics becomes essential, not a choice. Thus, mathematicians have been given a role in explaining such mathematics that make these things possible behind AI. Therefore, the authors wrote a textbook 'Basic Mathematics for Artificial Intelligence' by arranging the mathematics concepts and tools needed to understand AI and machine learning in one or two semesters, and organized lectures for undergraduate and graduate students of various majors to explore careers in artificial intelligence. In this paper, we share our experience of conducting this class with the full contents in http://matrix.skku.ac.kr/math4ai/.

• Journal of Appropriate Technology
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• v.6 no.2
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• pp.238-255
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• 2020

As COVID-19, which occurred at the end of 2019, has become a global pandemic, it has emerged as an unprecedented event that quickly destroys a nation's medical and healthcare system in both developed and developing countries. In the 21st century, most of the civil society that aimed for hyperconnected society is facing a new crisis that has not been experienced so far. Indeed, lack of personal protective equipment, isolation of clustered communities, disruption of medical systems necessary for diagnosis and treatment, and disruption of educational and economic activities due to social isolation are emerging. Since the COVID-19 has occurred, many of the difficulties that have occurred in the past six months indicate the basic infrastructure a society should have particularly in a pandemic. These include personal protective equipment (PPE), decontamination and quarantine tools essential for effective response, rapid and precise large-scale diagnosis, medical devices required for patient care, and identification and fast and wide on-line networks that can be used in social isolation. In this first part, we would like to introduce some representative examples of 1) personal protective equipment, 2) prevention of personal and community health, 3) social response through big data and networks within the framework of appropriate technology.

• Korean Journal of Clinical Laboratory Science
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• v.56 no.1
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• pp.10-20
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• 2024

RNA-sequencing (RNA-seq) is a technique used for providing global patterns of transcriptomes in samples. However, it can only provide the average gene expression across cells and does not address the heterogeneity within the samples. The advances in single-cell RNA sequencing (scRNA-seq) technology have revolutionized our understanding of heterogeneity and the dynamics of gene expression at the single-cell level. For example, scRNA-seq allows us to identify the cell types in complex tissues, which can provide information regarding the alteration of the cell population by perturbations, such as genetic modification. Since its initial introduction, scRNA-seq has rapidly become popular, leading to the development of a huge number of bioinformatic tools. However, the analysis of the big dataset generated from scRNA-seq requires a general understanding of the preprocessing of the dataset and a variety of analytical techniques. Here, we present an overview of the workflow involved in analyzing the scRNA-seq dataset. First, we describe the preprocessing of the dataset, including quality control, normalization, and dimensionality reduction. Then, we introduce the downstream analysis provided with the most commonly used computational packages. This review aims to provide a workflow guideline for new researchers interested in this field.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.835-845
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• 2013

Association rule of data mining techniques is the method to quantify the relevance between a set of items in a big database, andhas been applied in various fields like manufacturing industry, shopping mall, healthcare, insurance, and education. Philosophers of science have proposed interestingness measures for various kinds of patterns, analyzed their theoretical properties, evaluated them empirically, and suggested strategies to select appropriate measures for particular domains and requirements. Such interestingness measures are divided into objective, subjective, and semantic measures. Objective measures are based on data used in the discovery process and are typically motivated by statistical considerations. Subjective measures take into account not only the data but also the knowledge and interests of users who examine the pattern, while semantic measures additionally take into account utility and actionability. In a very different context, researchers have devoted a lot of attention to measures of confirmation or evidential support. The focus in this paper was on asymmetric confirmation measures, and we compared confirmation measures with basic association thresholds using some simulation data. As the result, we could distinguish the direction of association rule by confirmation measures, and interpret degree of association operationally by them. Futhermore, the result showed that the measure by Rips and that by Kemeny and Oppenheim were better than other confirmation measures.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.67-75
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• 2022

Medical information is variously generated not only from medical devices but also from electronic devices. Recently, related convergence technologies from big data collection in healthcare to medical AI products for patient's condition analysis are rapidly increasing. However, there are difficulties in applying them because of independent developmental procedures. In this paper, we propose an intelligent hospital information system (iHIS) model to simplify and integrate research, development and application of medical AI technology. The proposed model includes (1) real-time patient data management, (2) specialized data management for medical AI development, and (3) real-time monitoring for patient. Using this, real-time biometric data collection and medical AI specialized data generation from patient monitoring devices, as well as specific AI applications of camera-based patient gait analysis and brain MRA-based cerebrovascular disease analysis will be introduced. Based on the proposed model, it is expected that it will be used to improve the HIS by increasing security of data management and improving practical use through consistent interface platformization.

• Journal of Industrial Convergence
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• v.22 no.2
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• pp.97-103
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• 2024

The purpose of this study was to examine the impact of balance training on the Inbody and recovery of the balance capability in stroke patient with obesity. The exercise program was to conduct obesity group and normal weight group, 22 subjects were divided equally into experimental(obesity) and controlled group(normal weight), assigned to excercise using the balance training system for 30min a day and 5 days a week. Every pre and post-experimental data of both groups were gathered by Inbody and BSS(Biodex Medical Systems) for 8 weeks. As a result, Comparing the intra-group data measured by Inbody, obesity group showed significant difference in every parameter (p<.05). In the inter-group data, every parameter showed significant difference between both groups (p<.05). Comparing the intra-group data of LOS(Limits Of Stability), obesity group showed significant difference with all parameters, except with 'Backward' and 'Left' (p<.05). In the inter-group data, 'Forward' parameter showed significant difference. Comparing the intra-group data of PS(Postural Stability), obesity group showed significant difference with all parameters (p<.05). The inter-group PS(Postural Stability) results differed significantly only with 'Med/lat'(p=.000). The above results implicate about the following conclusions that the balance training had a big effect on the Inbody and recovery of the balance capability in stroke patient with obesity.

• Journal of the Health Care and Life Science
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• v.9 no.1
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• pp.103-115
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• 2021

The purpose of this study is to understand the annual trend of patients with cervical vertebrae disability and improve their health service utilization in the general description (200 TABLE) of patients with cervical vertebrae disability.The main results of this study are as follows. All patients with cervical vertebrae disability were women aged 50 to 59. Compared to 2010, the proportion of patients with disease increased year by year in all subjects in 2018, with men under 30-39 years of age and women under 19 years of age increasing the highest.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.12
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• pp.1589-1595
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• 2018

The purpose of this research is to search for and identify trends in adolescent problems on internet news sites. Among the domestic internet news sites, 8,110 articles on adolescent problems from 1993 to 2018 were analyzed for the top three top-ranked 'The Chosunilbo', 'The Dong-A Ilbo', and 'Korea Joongang Daily' news sites. As a result of this study, we have been able to understand the topic of adolescent problems in internet news sites for the last 26 years and find out that the trend of articles has been changed considering the environment, policies and culture related to adolescent problems. This study is meaningful to start from the method to examine the social trends of existing adolescent problems, to expand the scope of adolescent problems and counseling, to use quantitative analysis methods and to provide new information to consider diversity.

• Journal of Industrial Convergence
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• v.20 no.6
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• pp.7-15
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• 2022

Recently, due to the development of AI and big data technologies following the advent of the era of the 4th Industrial Revolution, the emerging metaverse industry is emerging as a new business, and in particular, from this point of view, this paper analyzes the history of metaverse and the pros and cons of "Geppetto", which is the most popular in the Korean metaverse market, and aims to give an appropriate direction for future development based on this. In order to carry out this study, we first used SWOT analysis techniques as an initial enterprise analysis method to examine the strengths and weaknesses, opportunities and threat requirements, and derive the status of each factor. Based on the factors in each of the subsequent derivatives, we wanted to explore the TOWS development strategy and present significant implications based on this.

• Journal of Preventive Medicine and Public Health
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• v.55 no.1
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• pp.1-9
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• 2022

An index that evaluates the health level of a population group considering both death and loss of function due to disease is called a summary measure of population health (SMPH). SMPHs are broadly divided into life year indices and life expectancy indices, the latter of which comprise healthy life expectancy (HLE). HLE is included as a policy target in various national and regional level healthcare plans, and the term "HLE" is commonly used in academia and by the public. However, the overall level of understanding of HLE-such as the precise definition of HLE and methods of calculating HLE-still seems to be low. As discussed in this study, the types of HLE are classified into disability-free life expectancy, disease-free life expectancy, quality-adjusted life expectancy, self-rated HLE, and disability-adjusted life expectancy. Their characteristics are examined to facilitate a correct understanding and appropriate utilization of HLE. In addition, the Sullivan method, as a representative method for calculating HLE, is presented in detail, and major issues in the process of calculating HLE, such as selection of the population group and age group, estimation of death probability, calculation of life years, and incorporation of health weights, are reviewed. This study will help researchers to select an appropriate HLE type and evaluate the validity of HLE research results, and it is expected to contribute to the vitalization of HLE research.