• 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.

• Journal of Creative Information Culture
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• v.7 no.4
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• pp.197-206
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• 2021

This study is a case of convergence education using the AI model of entry in elementary schools. The subject is English, and the class was conducted based on the image learning model among the convergence activities with the art department drawing and the AI model of the entry. In order to effectively achieve the learning goals of speaking and writing in English education. The class was designed by combining art and SW. Students experienced communication using AI, improved confidence, and were able to improve creativity and communication skills by expressing not only listening and speaking but also expressing through various media such as pictures and photos. In addition, in order to find out the effectiveness of the class, a survey was conducted on students and the results were analyzed. As a result of the analysis, it was found that it had a positive effect on students' participation rate, degree of understanding AI after class, interest in AI, satisfaction with AI classes.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.1-16
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• 2022

The current AI technology has been developing rapidly enough to realize or even exceed the level of abilities that only humans had in the past. In the near future, it is predicted that humans and AI will influence each other as members of the metaverse society. Therefore, this study emphasizes the importance of empathy as a core competency for humans to pursue happiness while maintaining the dignity of humans in the era when AI and humans will coexist in the metaverse. In this study, 'Digital Human Empathy Index (DHEI)' is developed that reflects the social nature of computer-mediated communication in the metaverse As a result, DHEI consisted of a total of 7 factors, which are Perspective Taking, Self/Other Awareness, Contextual Understanding of Systemic Barriers, Impact Assessment, Solidarity, Being Peaceful, and Anthropomorphism. This study is expected to contribute to setting the direction of future education by suggesting a new measure of empathy.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.3
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• pp.303-323
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• 2023

The purpose of this study is to introduce this language model in the era of generative AI such as ChatGPT, and to provide direction for data literacy education components in libraries using it. To this end, the following three research questions are proposed. First, the technical features of ChatGPT-like language models are examined, and then, it is argued that data literacy education is necessary for the proper and accurate use of information by users using a service platform based on generative AI technology. Finally, for library data literacy education in the ChatGPT era, it is proposed a data literacy education scheme including seven components such as data understanding, data generation, data collection, data verification, data management, data use and sharing, and data ethics. In conclusion, since generative AI technologies such as ChatGPT are expected to have a significant impact on users' information utilization, libraries should think about the advantages, disadvantages, and problems of these technologies first, and use them as a basis for further improving library information services.

• Journal of Fashion Business
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• v.27 no.4
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• pp.141-162
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• 2023

With the prospect that integrating creative AI in the fashion design field will become more visible, this study considered the case of creative fashion design development through Human-AI Co-creation (HAIC). Methodologically, this research encompasses a literature review and empirical investigations. In the literature review, the fashion design and creative HAIC processes, and the possibilities of integrating AI in fashion design were considered. In the empirical study, based on the case analysis of generating fashion design through HAIC, the HAIC type according to the role and interaction method, and characteristics of humans and AI was considered, and the HAIC process for fashion design was derived. The results of this study are summarized as follows. First, HAIC types in fashion design are divided into four types: AI-driven passive HAIC, human-driven passive HAIC, flexible interaction-based HAIC, and integrated interaction-based value creation HAIC. Second, the stages of the HAIC process for creative fashion design can be broadly divided into semantic data integration, visual ideation, design creation and expansion, design presentation, and design/manufacturing solution and UX platform creation. Third, in fashion design, HAIC contributes to human ability, enhancement of creativity, achievement of efficient workflow, and creation of new values. This research suggests that HAIC has the potential to revolutionize the fashion design industry by facilitating collaboration between humans and AI; consequently, enhancing creativity, and improving the efficiency of the design process. It also offers a framework for understanding the different types of HAIC and the stages involved in the creative fashion design process.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.59-67
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• 2021

The development of AI technology has brought about a big change in our lives. As AI's influence grows from life to society to the economy, the importance of education on AI and data is also growing. In particular, the OECD Education Research Report and various domestic information and curriculum studies address data literacy and present it as an essential competency. Looking at domestic and international studies, one can see that the definition of data literacy differs in its specific content and scope from researchers to researchers. Thus, the definition of major research related to data literacy was analyzed from various angles and derived from various angles. In key studies, Word2vec natural language processing methods, along with word frequency analysis used to define data literacy, are used to analyze semantic similarities and nominate them based on content elements of curriculum research to derive the definition of 'understanding and using data to process information'. Based on the definition of data literacy derived from this study, we hope that the contents will be revised and supplemented, and more research will be conducted to provide a good foundation for educational research that develops students' future capabilities.

• Science of Emotion and Sensibility
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• v.26 no.4
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• pp.115-124
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• 2023

This study explores the intersection of literary studies and artificial intelligence (AI), focusing on the common theme of human emotions to foster complementary advancements in both fields. By adopting a comparative perspective, the paper investigates emotion as a shared focal point, analyzing various emotion-related concepts from both literary and AI perspectives. Despite the scarcity of research on the fusion of AI and literary studies, this study pioneers an interdisciplinary approach within the humanities, anticipating future developments in AI. It proposes that literary sensibility can contribute to AI by formalizing subjective literary emotions, thereby enhancing AI's understanding of complex human emotions. This paper's methodology involves the terminology-centered extraction of emotions, aiming to blend subjective imagination with objective technology. This fusion is expected to not only deepen AI's comprehension of human complexities but also broaden literary research by rapidly analyzing diverse human data. The study emphasizes the need for a collaborative dialogue between literature and engineering, recognizing each field's limitations while pursuing a convergent enhancement that transcends these boundaries.

• Korean Journal of Radiology
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• v.25 no.4
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• pp.343-350
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• 2024

Objective: Artificial intelligence-based computer-aided diagnosis (AI-CAD) is increasingly used in mammography. While the continuous scores of AI-CAD have been related to malignancy risk, the understanding of how to interpret and apply these scores remains limited. We investigated the positive predictive values (PPVs) of the abnormality scores generated by a deep learning-based commercial AI-CAD system and analyzed them in relation to clinical and radiological findings. Materials and Methods: From March 2020 to May 2022, 656 breasts from 599 women (mean age 52.6 ± 11.5 years, including 0.6% [4/599] high-risk women) who underwent mammography and received positive AI-CAD results (Lunit Insight MMG, abnormality score ≥ 10) were retrospectively included in this study. Univariable and multivariable analyses were performed to evaluate the associations between the AI-CAD abnormality scores and clinical and radiological factors. The breasts were subdivided according to the abnormality scores into groups 1 (10-49), 2 (50-69), 3 (70-89), and 4 (90-100) using the optimal binning method. The PPVs were calculated for all breasts and subgroups. Results: Diagnostic indications and positive imaging findings by radiologists were associated with higher abnormality scores in the multivariable regression analysis. The overall PPV of AI-CAD was 32.5% (213/656) for all breasts, including 213 breast cancers, 129 breasts with benign biopsy results, and 314 breasts with benign outcomes in the follow-up or diagnostic studies. In the screening mammography subgroup, the PPVs were 18.6% (58/312) overall and 5.1% (12/235), 29.0% (9/31), 57.9% (11/19), and 96.3% (26/27) for score groups 1, 2, 3, and 4, respectively. The PPVs were significantly higher in women with diagnostic indications (45.1% [155/344]), palpability (51.9% [149/287]), fatty breasts (61.2% [60/98]), and certain imaging findings (masses with or without calcifications and distortion). Conclusion: PPV increased with increasing AI-CAD abnormality scores. The PPVs of AI-CAD satisfied the acceptable PPV range according to Breast Imaging-Reporting and Data System for screening mammography and were higher for diagnostic mammography.

• The Journal of Korean Medicine
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• v.44 no.4
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• pp.72-86
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• 2023

Objectives: The medical field is rapidly evolving with AI and digital technologies like AI-based X-ray analysis and digital therapeutics gaining approval. Telemedicine is becoming prominent, and medical schools are adapting by integrating AI education. Pusan National University leads a talent training project for AI in health. Korean Medicine is incorporating AI with diagnostic systems and chatbots. However, there's a lack of research on education awareness in Korean Medicine Colleges. The study aims to assess opinions on integrating AI, digital therapeutics, and DNA test into the Korean medicine college curriculum for improved education. Methods: We selected appropriate four specific areas: artificial intelligence in medicine, digital therapeutics, DNA test, and telemedicine. The questionnaire developed for this study underwent expert evaluation and was subsequently administered to registered KMDs of the Association of Korean Medicine, as well as students from 12 Korean Medicine universities. The survey was designed to analyze the awareness and perceived importance of the 4 areas. Results: Both KMDs and Korean medicine students exhibited comparable awareness levels across the four objectives. Notably, both groups identified a high educational necessity and importance of artificial intelligence in medicine for clinical settings. Statistically significant differences were observed between KMDs and students in their perspectives on the importance of telemedicine and DNA test in the Korean medicine field, the educational necessity of DNA test within Korean medicine universities, and the need for comprehension of regulations related to digital therapeutics. Conclusion: The survey of Korean medicine professionals and students underscores a strong understanding of key areas such as Telemedicine, medical AI, DNA test, and digital therapeutics. Medical AI is identified as crucial for future education. There's a consensus on the need for curriculum changes in Korean medicine schools, particularly in adapting to evolving healthcare trends. The focus should be on practical clinical application, with a call for additional research to better integrate student and practitioner perspectives in future curriculum reform discussions.

• Journal of muscle and joint health
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• v.28 no.3
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• pp.217-222
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• 2021

Background: The reaction of nurses to the advent of artificial intelligence (AI) during the fourth industrial revolution era remains questionable. Understanding Florence Nightingale's achievements may provide valuable lessons that will be helpful to contemporary nurses. Aims: To understand Nightingale's nursing philosophy and methods and provide suggestions for future nursing practice, education, research, and health policy. Source of evidence: Literature. Discussion/Conclusion: Just as Nightingale captured the situation of her time and introduced latest scientific methods, modern nurses need to learn from Nightingale's drastic actions to meet social needs. Nursing can regain a solid humanistic foundation by returning to core values of nursing and humanities, while simultaneously adopting state-of-the-art technologies. Implications for Nursing Policy: AI-driven technologies will advance nursing services and provide greater human-centered and personalized care by eliminating iterative and labor-intensive tasks. Nursing educational policy should support the advancement of nursing curricula to develop AI competencies and specialists within the nursing field.