• International Journal of Contents
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• v.18 no.3
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• pp.49-57
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• 2022

The purpose of this study was to investigate the satisfaction of personnel selection process according to type of personnel manager and to examine whether the relationship between the type of personnel manager and the satisfaction with the personnel selection process was moderated by the applicant's perception of procedural justice. This study was conducted using a between-group design with 208 students from a four-year university in Korea. One group watched a video in which a human personnel manager selected employees and the other group watched a video in which an AI personnel manager selected employees. Participants were randomly assigned to a condition, responded to a demographic questionnaire, and answered measures of procedural justice and satisfaction with personnel selection after watching the video. As a result, the selection process satisfaction was significantly higher when the human personnel manager conducted the selection process than when the AI personnel manager conducted such process. In addition, when procedural justice was perceived as low, there was a significant difference in satisfaction between human and AI groups. However, when procedural justice was perceived as high, there was no significant difference in satisfaction between the two groups. Based on study results, the significance and limitations of this study and suggestions for future studies are discussed.

• Korean Medical Education Review
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• v.18 no.2
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• pp.51-57
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• 2016

This literature review explores artificial intelligence (AI) technology trends and IBM Watson health and medical references. This study explains how healthcare will be changed by the evolution of AI technology, and also summarizes key technologies in AI, specifically the technology of IBM Watson. We look at this issue from the perspective of 'information overload,' in that medical literature doubles every three years, with approximately 700,000 new scientific articles being published every year, in addition to the explosion of patient data. Estimates are also forecasting a shortage of oncologists, with the demand expected to grow by 42%. Due to this projected shortage, physicians won't likely be able to explore the best treatment options for patients in clinical trials. This issue can be addressed by the AI Watson motivation to solve healthcare industry issues. In addition, the Watson Oncology solution is reviewed from the end user interface point of view. This study also investigates global company platform business to explain how AI and machine learning technology are expanding in the market with use cases. It emphasizes ecosystem partner business models that can support startup and venture businesses including healthcare models. Finally, we identify a need for healthcare company partnerships to be reviewed from the aspect of solution transformation. AI and Watson will change a lot in the healthcare business. This study addresses what we need to prepare for AI, Cognitive Era those are understanding of AI innovation, Cloud Platform business, the importance of data sets, and needs for further enhancement in our knowledge base.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.215-235
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• 2024

As artificial intelligence (AI) technology is recognized as a key technology that will determine future national competitiveness, competition for AI technology and industry promotion policies in major countries is intensifying. This study aims to present implications for domestic policy making by analyzing the policies of major countries on the start-up of AI companies, which are the basis of the AI industry ecosystem. The top four countries and the EU for the number of new investment attraction companies in the 2023 AI Index announced by the HAI Research Institute at Stanford University in the United States were selected, The United States enacted the National AI Initiative Act (NAIIA) in 2021. Through this law, The US Government is promoting continued leadership in the United States in AI R&D, developing reliable AI systems in the public and private sectors, building an AI system ecosystem across society, and strengthening DB management and access to AI policies conducted by all federal agencies. In the 14th Five-Year (2021-2025) Plan and 2035 Long-term Goals held in 2021, China has specified AI as the first of the seven strategic high-tech technologies, and is developing policies aimed at becoming the No. 1 AI global powerhouse by 2030. The UK is investing in innovative R&D companies through the 'Future Fund Breakthrough' in 2021, and is expanding related investments by preparing national strategies to leap forward as AI leaders, such as the implementation plan of the national AI strategy in 2022. Israel is supporting technology investment in start-up companies centered on the Innovation Agency, and the Innovation Agency is leading mid- to long-term investments of 2 to 15 years and regulatory reforms for new technologies. The EU is strengthening its digital innovation hub network and creating the InvestEU (European Strategic Investment Fund) and AI investment fund to support the use of AI by SMEs. This study aims to contribute to analyzing the policies of major foreign countries in making AI company start-up policies and providing a basis for Korea's strategy search. The limitations of the study are the limitations of the countries to be analyzed and the failure to attempt comparative analysis of the policy environments of the countries under the same conditions.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.15
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• pp.6359-6364
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• 2015

Background: Preclinical studies have shown that the combination of an aromatase inhibitor (AI) and capecitabine in estrogen receptor (ER)- positive cell lines enhance antitumor efficacy. This retrospective analysis of a group of patients with metastatic breast cancer (MBC) evaluated the efficacy and safety of combined AI with capecitabine. Materials and Methods: Patients with hormone receptor-positive metastatic breast cancer treated between 1st January 2005 and 31st December 2010 with a combination of capecitabine and AI were evaluated and outcomes were compared with those of women treated with capecitabine in conventional dose or AI as a monotherapy. Results: Of 72 patients evaluated, 31 received the combination treatment, 22 AI and 19 capecitabine. The combination was used in 20 patients as first-line and 11 as second-line treatment. Mean age was 46.2 years with a range of 28-72 years. At the time of progression, 97% had a performance status of <2 and 55% had visceral disease. No significant difference was observed between the three groups according to clinical and pathological features. Mean follow up was 38 months with a range of 16-66 months. The median PFS of first-line treatment was significantly better for the combination (PFS 21 months vs 8.0 months for capecitabine and 15.0 months for AI). For second-line treatment, the PFS was longer in the combination compared with capecitabine and Al groups (18 months vs. 5.0 months vs. 11.0 months, respectively). Median 2 year and 5 year survival did not show any significant differences among combination and monotherapy groups. The most common adverse events for the combination group were grade 1 and 2 hand-for syndrome (69%), grade 1 fatigue (64%) and grade 1 diarrhoea (29%). Three grade 3 hand-foot syndrome events were reported. Conclusions: Combination treatment with capecitabine and AI used as a first line or second line treatment was safe with much lowered toxicity. Prospective randomized clinical trials should evaluate the use of combination therapy in advanced breast cancer to confirm these findings.

• Journal of Nutrition and Health
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• v.41 no.1
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• pp.100-110
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• 2008

The present study estimates intake levels of dietary fiber (DF) in Korean adults aged 20 and over, using a newly established dietary fiber database for 3,149 food items, as well as 24-hour recall method data from the 2001 Korean National Health and Nutrition Survey. Dietary fiber intake and food groups are analyzed by gender, age, and region. The average dietary fiber intake, per capita of Korea was estimated to be 12.24g/1,000kcal or 23.58g/day. Calorie-based dietary fiber intake for 20-49 year-old-Korean males, 20-29 year-old females, and the adults who resided in metropolitan areas was under the Adequate Intake for DF, 12 g/1,000 kcal. Further, the dietary fiber intake after adjusting energy intake in people over 75 year-old was estimated to be 75% of AI. Vegetables, cereals and fruits were three major sources of DF for Korean, making up approximately 75% of DF. Regarding the subjects of this study, major sources of dietary fiber were Kimchi and well-polished rice, which supplied 13.98% and 9.16% of total dietary fiber intake, respectively. The result of this study could contribute to the establishment of DRIs for dietary fiber, after adjusting energy intake for Korean aged 75 years and over. The beneficial health effects of DF and the necessity of nutritional education in this area should be continuously emphasized concerning 20-29 year-old people and metropolitan adults.

• Journal of Digestive Cancer Research
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• v.11 no.3
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• pp.130-140
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• 2023

Gastric cancer (GC) is one of the most common malignant tumors worldwide, with a 5-year survival rate of < 40%. The diagnosis and treatment decisions of GC rely on human experts' judgments on medical images; therefore, the accuracy can be hindered by image condition, objective criterion, limited experience, and interobserver discrepancy. In recent years, several applications of artificial intelligence (AI) have emerged in the GC field based on improvement of computational power and deep learning algorithms. AI can support various clinical practices in endoscopic examination, pathologic confirmation, radiologic staging, and prognosis prediction. This review has systematically summarized the current status of AI applications after a comprehensive literature search. Although the current approaches are challenged by data scarcity and poor interpretability, future directions of this field are likely to overcome the risk and enhance their accuracy and applicability in clinical practice.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.6
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• pp.843-852
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• 2022

Despite continuous safety management, the death rate of construction workers is not decreasing every year. Accordingly, various studies are in progress to prevent construction site accidents. In this paper, we developed an AI-based priority inspection target selection model that preferentially selects sites are expected to cause construction accidents among construction sites with construction costs of less than 5 billion won (KRW). In particular, Random Forest (90.48 % of accident prediction AUC-ROC) showed the best performance among applied AI algorithms (Classification analysis). The main factors causing construction accidents were construction costs, total number of construction days and the number of construction performance evaluations. In this study an ROI (return of investment) of about 917.7 % can be predicted over 8 years as a result of better efficiency of manual inspections human resource and a preemptive response to construction accidents.

• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.109-135
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• 2021

his study classified the development process of artificial intelligence (AI) speakers through analysis of the news text of artificial intelligence (AI) speakers shown in traditional news reports, and identified the characteristics of each product by period. The theoretical background used in the analysis are news frames and topic frames. As analysis methods, topic modeling and semantic network analysis using the LDA method were used. The research method was a content analysis method. From 2014 to 2019, 2710 news related to AI speakers were first collected, and secondly, topic frames were analyzed using Nodexl algorithm. The result of this study is that, first, the trend of topic frames by AI speaker provider type was different according to the characteristics of the four operators (communication service provider, online platform, OS provider, and IT device manufacturer). Specifically, online platform operators (Google, Naver, Amazon, Kakao) appeared as a frame that uses AI speakers as'search or input devices'. On the other hand, telecommunications operators (SKT, KT) showed prominent frames for IPTV, which is the parent company's flagship business, and 'auxiliary device' of the telecommunication business. Furthermore, the frame of "personalization of products and voice service" was remarkable for OS operators (MS, Apple), and the frame for IT device manufacturers (Samsung) was "Internet of Things (IoT) Integrated Intelligence System". The econd, result id that the trend of the topic frame by AI speaker development period (by year) showed a tendency to develop around AI technology in the first phase (2014-2016), and in the second phase (2017-2018), the social relationship between AI technology and users It was related to interaction, and in the third phase (2019), there was a trend of shifting from AI technology-centered to user-centered. As a result of QAP analysis, it was found that news frames by business operator and development period in AI speaker development are socially constituted by determinants of media discourse. The implication of this study was that the evolution of AI speakers was found by the characteristics of the parent company and the process of co-evolution due to interactions between users by business operator and development period. The implications of this study are that the results of this study are important indicators for predicting the future prospects of AI speakers and presenting directions accordingly.

• Journal of Chest Surgery
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• v.26 no.11
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• pp.821-826
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• 1993

Between January 1983 and December 1992, we had experienced 79 patients of ventricular septal defect [ VSD ] associated with aortic insufficiency [AI] which constitute 4.6 % of total numbers of VSD. The mean age of the patients was 10.2 years with a range of 1 to 35 years and the average degree of aortic insufficiency classified by Sellers was 2.1. The type of VSD was subpulmonic in 57 patients and perimembranous in 22. Most common pathologic finding causing AI was prolapse of right coronary cusp [ 54 cases ; 71.4% ] ,followed by prolapse of both right and non-coronary cusp[ 12 cases ; 7.9% ]. VSD closure alone was performed in 51 patients and their mean age was 7.7 years [ ranged 1 to 13 years ]. VSD closure and aortic valve reconstruction was performed in 22 patients, VSD closure and aortic valve replacement in 6 patients, and the mean age of the patients was 14.5 years [ ranged 2 to 28 years ], 20.4 years [ ranged 18 to 35 years ] respectively. There was no hospital mortality. All patients were followed up from 1 month to 9 year 4 months [average; 21.4 months ] and there was one late death. Our data suggests that, early closure of VSD without any manipulation on the valve may be sufficient procedure to improve or at least withhold progression of AI in children and furthermore patients with VSD associated AI should be corrected promptly after diagnosis.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.83-92
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• 2023

The purpose of this research is to develop a creative education program that utilizes AI education program based on big data for general education high schools, and to investigate its effectiveness. In order to achieve the purpose of the research, we developed a creative education program using artificial intelligence based on big data for first-year general high school students, and carried out on-site classes at schools and a validation process by experts. In order to measure the creative problem-solving ability and class satisfaction of high school students, a creative problem-solving ability test was conducted before and after the program application, and a class satisfaction test was conducted after the program. The results of this study are as follows. First, AI education program based on big data were statistically effective to improve the creative problem solving ability according to independent sample t test about 'problem discovery and analysis', 'idea generation', 'execution plan', 'conviction and communication', and 'innovation tendency' except 'execution', 'the difference between pre- and post-scores of male student and female student' on first year high school students. Secondly, in satisfaction conducted after classes of AI education program based on big data, the average of 'Satisfaction', 'Interest', 'Participation', 'Persistence' were 3.56 to 3.92, and the overall average was 3.78. Therefore, it was investigated that there was a lesson effect of the AI education program based on big data developed in this research.