• 디지털산업정보학회논문지
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• 제19권4호
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• pp.97-115
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• 2023

In South Korea, chronic kidney disease(CKD) impacts around 4.6 million adults, leading to a high reliance on hemodialysis. For effective dialysis, vascular access is crucial, with decisions about vascular surgeries often made during dialysis sessions. Anticipating these needs could improve dialysis quality and patient comfort. This study investigates the use of Artificial Intelligence(AI) to predict the timing of surgeries for dialysis vessels, an area not extensively researched. We've developed an AI algorithm using predictive maintenance methods, transitioning from machine learning to a more advanced deep learning approach with Long Short-Term Memory(LSTM) models. The algorithm processes variables such as venous pressure, blood flow, and patient age, demonstrating high effectiveness with metrics exceeding 0.91. By shortening the data collection intervals, a more refined model can be obtained. Implementing this AI in clinical practice could notably enhance patient experience and the quality of medical services in dialysis, marking a significant advancement in the treatment of CKD.

• Korean Journal of Acupuncture
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• 제41권1호
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• pp.27-32
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• 2024

Objectives : This study developed an AI-based patient chatbot and examined the usability and educational effectiveness of the chatbot in the context of Korean medicine education. Methods : The patient chatbot was developed using the AI chatbot builder 'Danbee', and a total of five experts were surveyed and interviewed to determine the usability, effectiveness, advantages, disadvantages, and improvement points of the chatbot. Results : The patient chatbot was found to have high usability and educational effectiveness. The advantages of the patient chatbot were 1) it provided students with practical experience in performing clinical skills, 2) it provided instructors with assessment materials while reducing their teaching burden, and 3) it could be effectively used for horizontal and vertical integration education. The disadvantages and improvements of the patient chatbot were 1) improving the accuracy of intention inference, 2) providing students with specific instructions for problem-solving activities, and 3) providing assessment results and feedback about students' activities. Conclusions : This study is significant in that it proposes a new training method to overcome the limitations of the existing doctor-patient simulation. It is hoped that this study will stimulate further research on the improvement of students' clinical skills using artificial intelligence.

• Korean Journal of Radiology
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• 제23권5호
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• pp.505-516
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• 2022

Objective: To evaluate whether artificial intelligence (AI) for detecting breast cancer on mammography can improve the performance and time efficiency of radiologists reading mammograms. Materials and Methods: A commercial deep learning-based software for mammography was validated using external data collected from 200 patients, 100 each with and without breast cancer (40 with benign lesions and 60 without lesions) from one hospital. Ten readers, including five breast specialist radiologists (BSRs) and five general radiologists (GRs), assessed all mammography images using a seven-point scale to rate the likelihood of malignancy in two sessions, with and without the aid of the AI-based software, and the reading time was automatically recorded using a web-based reporting system. Two reading sessions were conducted with a two-month washout period in between. Differences in the area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, and reading time between reading with and without AI were analyzed, accounting for data clustering by readers when indicated. Results: The AUROC of the AI alone, BSR (average across five readers), and GR (average across five readers) groups was 0.915 (95% confidence interval, 0.876-0.954), 0.813 (0.756-0.870), and 0.684 (0.616-0.752), respectively. With AI assistance, the AUROC significantly increased to 0.884 (0.840-0.928) and 0.833 (0.779-0.887) in the BSR and GR groups, respectively (p = 0.007 and p < 0.001, respectively). Sensitivity was improved by AI assistance in both groups (74.6% vs. 88.6% in BSR, p < 0.001; 52.1% vs. 79.4% in GR, p < 0.001), but the specificity did not differ significantly (66.6% vs. 66.4% in BSR, p = 0.238; 70.8% vs. 70.0% in GR, p = 0.689). The average reading time pooled across readers was significantly decreased by AI assistance for BSRs (82.73 vs. 73.04 seconds, p < 0.001) but increased in GRs (35.44 vs. 42.52 seconds, p < 0.001). Conclusion: AI-based software improved the performance of radiologists regardless of their experience and affected the reading time.

• 실천공학교육논문지
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• 제15권2호
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• pp.529-538
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• 2023

보편적 인공지능교육의 필요성이 확대되고 직무 변화가 이루어지고 있는 현 시점에서, 가장 먼저 인공지능을 직무의 일부분으로 경험하게 되는 대학의 비전공자를 위한 인공지능 교양교육에 대한 연구 및 논의는 미흡한 실정이다. 비전공자 대상 인공지능 교육과정이 운영되고 있지만 주로 인공지능의 개념 및 원리에 대한 이론 중심의 교육으로 운영되고 있다. 비전공자 대상 인공지능에 대한 일반적인 개념을 이해하기 위해 체험학습을 병행하여 진행 할 필요가 있다. 따라서 본 연구는 비전공자의 특성을 고려하여 학습에 흥미를 갖고, 인공지능 수업에 대한 부담감을 낮출 수 있는 난이도의 인공지능 체험교육 학습콘텐츠를 설계한 후 앱인벤터와 오렌지 인공지능 플랫폼을 활용한 체험 교육의 학습효과를 살펴보고자 한다. 팀 별 인공지능 관련 프로젝트 작성을 통해 수집된 학습관련 데이터와 설문조사 자료를 바탕으로 분석한 결과 인공지능 교육의 필요성에 대한 인식의 긍정적인 변화와 인공지능 리터러시 능력이 향상된 것으로 나타났다. 교수자에게는 인공지능 체험교육 학습을 위한 학습모형을 설계하는 데 기틀을 마련해 주는 계기가 될 것으로 기대한다.

• 한국융합학회논문지
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• 제12권8호
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• pp.115-122
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• 2021

본 연구는 최근 활발하게 진행되고 있는 AI 기반의 프로그래매틱 광고 전략 중 개인화 광고와 맞춤화 광고전략이 소비자의 광고태도에 어떤 영향을 미치는지를 살펴보고자 하였다. 이를 위하여 두 광고 전략을 선행변인으로 설정하여 행동 과정에서 발생하는 총체적 감정 경험인 트랜스포테이션을 거쳐 광고태도에 이르는 영향 관계를 살펴보았다. 일반인 110명을 대상으로 조사한 결과, 개인화 광고는 소비자의 트랜스포테이션에 영향력이 유의미하지 않았으나, 맞춤화 광고 전략이 정(+)적 영향력을 미치고 있었다. 또한, 트렌스포테이션은 광고태도에 정(+)의 영향력을 가지고 있었다. 이러한 결과는 소비자의 적극적 선택으로 만들어진 맞춤화 광고 상황은 소비자의 긍정적 감정 경험을 유도할 수 있으므로, 기업의 기계적인 분석과 노출 중심의 광고 전략보다는 소비자를 적극적으로 광고 선택 상황 즉, 맞춤화 광고상황으로 유도해야 할 필요성을 제시하고 있다.

• 한국비블리아학회지
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• 제33권1호
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• pp.139-166
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• 2022

본 연구는 5G 신기술에 가장 민감한 세대의 윤리 행태를 권장하는 일환으로 미래 정보전문가를 희망하는 주체를 위한 윤리 리터러시(Ethics-Literacy) 교육과정모형 개발을 목적으로 한다. 연구 범위의 핵심 주제인 5G 특성, 리터러시, 윤리 쟁점, 6C 역량기반 교육, 이용자 경험 등을 주제어로 최근 5년 이내(2022-2017) 출간된 국내외 학술 연구자료를 조사하고 내용분석으로 최종 86편을 연구대상으로 선정하여 문헌 연구가 진행되었다. 분석 결과가 제시하는 것은 첫째, 기존의 리터러시는 5G 환경에 대응된 네 영역으로 구분될 수 있고 둘째, 분석된 윤리 쟁점은 모든 리터러시 영역에서 보이는 공통 쟁점과 각 리터러시 영역별 특수 쟁점으로 비교 구분되었다. 분석된 결과와 4차 산업혁명 교육방식으로 제시된 6C 역량기반 교육을 바탕으로 대학 차원의 5G 정보환경 정보전문가를 위한 윤리 리터러시 교육과정모형을 개발하여 제시하였다.

• 한국인터넷방송통신학회논문지
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• 제24권2호
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• pp.79-86
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• 2024

본 논문에서는 기존의 내용 전달 위주의 학습 메타버스 플랫폼이 아닌 실제 수업 활동에서 이루어지는 다양한 학습 상호작용에 기반한 가상 학습 플랫폼을 제안한다. 본 연구에서는 AI와 가상환경을 융합한 학습 환경을 제공하여 실시간 AI와 대화하며 문제를 풀어가는 방식을 활용하고 있다. 또한, 수업의 몰입도를 향상하기 위해 G-러닝 기법을 적용하였다. 본 연구를 통해 개발한 VirtualEdu 플랫폼은 자기주도적 학습, 게임을 통한 흥미 유발, 그리고 PBL 수업 방식을 조합하여 효과적인 학습 경험을 제공하고 있다. 이를 기반으로 학생들의 참여도와 학습 효과를 향상 시키는 새로운 교육 방식을 제안하고 있다. 실험으로는 50명 이상의 학습자가 실시간 화상 학습 활동 기반의 다양한 학습 활동애 대해 성능 실험을 하였고, 결과로서 안정하게 원활한 수업이 진행됨을 얻을 수 있었다.

• 한국정보시스템학회지:정보시스템연구
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• 제4권
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• pp.181-209
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• 1995

As the effective use of information has gained greater attention over the decade, various conventional AI techniques have been applied to develop expert systems for business applications. Case-based reasoning (CBR) makes data more accessible by organizing it as a set of examples from past experience that can be generalized and applied to current problems. This paper illustrates basic concepts of CBR and addresses the system discussed in this paper can provide a basis for building more flexible and adaptable expert systems for business applications.

• 한국정보시스템학회지:정보시스템연구
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• 제28권4호
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• pp.223-250
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• 2019

Purpose As the 4th Industrial Revolution proceeded, attempts to direct and utilize information technology such as robots and drones in plays have been active. Information technology, such as AI or media art, which is applied in the production of theater productions, shapes the possibility of expressing the difficulty of actors, the effectiveness of dramatic effects, and the illusion. Despite the inconsistent effects of information technology on theatrical studies, little has been done despite the fact that the research on what factors affect the audience's satisfaction through the play. Hence, The purpose of this study is to demonstrate the characteristics of information technology and theater, especially audience's revisit intention. Design/methodology/approach The research model combining the theory of task-technology fit and the experience-economic model is presented. Findings The results of the empirical analysis suggest that the fit of information technology and theatrical task enriches the audience's experience and has a beneficial effect on the dissemination and export of contents management of art management in terms of revisit as a consumer and production of theatrical performing arts. This leads to the conclusion that task-technical fit and experiential economy could be applied to the field of performing arts in theater. It may also give useful implications to related producers such as producers, directors, and actors.

• 한국멀티미디어학회논문지
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• 제25권2호
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• pp.166-175
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• 2022

Digital transformation is driving so many changes in daily life and industry. The automobile industry is in a similar situation. In some cases, element techniques in areas called metabuses are also being adopted, such as 3D animated digital cockpit, around view, and voice AI, etc. Through the growth of the mobile market, the norm of human-computer interaction (HCI) has been evolving from keyboard-mouse interaction to touch screen. The core area was the graphical user interface (GUI), and recently, the audio user interface (AUI) has partially replaced the GUI. Since it is easy to access and intuitive to the user, it is quickly becoming a common area of the in-vehicle experience (IVE), especially. The benefits of a AUI are freeing the driver's eyes and hands, using fewer screens, lower interaction costs, more emotional and personal, effective for people with low vision. Nevertheless, when and where to apply a GUI or AUI are actually different approaches because some information is easier to process as we see it. In other cases, there is potential that AUI is more suitable. This is a study on a proposal to actively apply a AUI in the near future based on the context of various scenes occurring to improve IVE.