• Journal of the Korea Society of Computer and Information
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• v.25 no.9
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• pp.173-182
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• 2020

The purpose of this paper is to study the influence of new service methods of "artificial intelligence (AI) + medical cosmetology", a new service means, on customers' purchase intentions. To AI medical beauty APP sales as an empirical study. This paper designed Likert seven scale to investigate, using SPSS 24.0 statistical analysis software and AMOS24.0 structural equation software to analyze the survey data. The analysis method uses reliability analysis, validity analysis, and construct equation model analysis. Through empirical research, the following results can be found, 1. The system quality of AI medical beauty app will have a positive impact on perceived usefulness and perceived ease of use. 2. The information quality of AI medical beauty app will have a positive impact on perceived ease of use and perceived usefulness. 3. The service quality of AI medical beauty app will have a positive impact on perceived ease of use and perceived usefulness 4. Consumers' perceived ease of use has a positive impact on perceived usefulness and purchase intention. 5. The usefulness of consumers' notification has a positive effect on purchase intention.

• Journal of the Korean Society of Radiology
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• v.81 no.6
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• pp.1290-1304
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• 2020

Medical image analyses have been widely used to differentiate normal and abnormal cases, detect lesions, segment organs, etc. Recently, owing to many breakthroughs in artificial intelligence techniques, medical image analyses based on deep learning have been actively studied. However, sufficient medical data are difficult to obtain, and data imbalance between classes hinder the improvement of deep learning performance. To resolve these issues, various studies have been performed, and data augmentation has been found to be a solution. In this review, we introduce data augmentation techniques, including image processing, such as rotation, shift, and intensity variation methods, generative adversarial network-based method, and image property mixing methods. Subsequently, we examine various deep learning studies based on data augmentation techniques. Finally, we discuss the necessity and future directions of data augmentation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.511-513
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• 2022

Digital Health Care is the convergence of ICT and (non)medical technology, emphasizing the importance of prevent and monitoring health management in terms of new challenging medical paradigm: predictive, preventive, personalized and participatory. Beyond the limited medical industry of long-term care insurance, it is emerging that AI, IoT, Big Data related new services with new technologies in the 4^th revolution era. It is also noted that business field based on test bed is emergent; Caring Robot, wearable devices need to be launched in the market. Diverse service is possible with Big Data and AI etc.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.404-406
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• 2021

In modern society, artificial intelligence and automation are being applied in various fields due to the development of the 4th industrial revolution and IoT technology. In particular, systems with a high proportion of image processing, such as automated processes, intelligent CCTV, medical industry, robots, and drones, are susceptible to external factors noise. In this paper, we propose a digital filter based on noise estimation and weights to reconstruct an image in a complex noise environment. The proposed algorithm classifies the types of noise using noise judgment, and determines the noise level of the filtering mask to switch the filtering process to obtain the final output. In order to verify the performance of the proposed algorithm, simulation was conducted, compared with the existing filter algorithm, and the results were analyzed.

• Journal of Digital Convergence
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• v.18 no.6
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• pp.311-321
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• 2020

The purpose of the study is to verify the effectiveness the Freshman Preliminary Health Administrators(FPHA)' Empathic Problem Solving Ability(EPSA) through the application of Medical Service Design Thinking(MSDT) conducted by undergraduate school of SNS hospital marketing education. The pre-post questionnaire survey was conducted on 39 students in the freshman year of the Department of Health Administration after applying MSDT for 15 weeks from September to December, 2019 at a college in Daegu. MSDT was positive influenced on the improvement of Empathic Imagine, Empathic interest, Empathic awakening of the FPHA' EPSA. In the analysis of key common words, the use of neutral and negative words was low, while the use of positive words was high. In order to systematically equip Empathic problem solving job competency in the age of artificial intelligence, it is meaningful to develop a program for the freshmen curriculum and to conduct a analysis of the structured and unstructured data to verify its effectiveness. Additional program development research is needed for the application of theoretical subjects.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.85-92
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• 2023

Deep learning applications are increasingly being leveraged for disease detection tasks in medical imaging modalities such as X-ray, Computed Tomography (CT), and Magnetic Resonance Imaging (MRI). Most data-centric deep learning challenges necessitate the use of supervised learning methodologies to attain high accuracy and to facilitate performance evaluation through comparison with the ground truth. Supervised learning mandates a substantial amount of image and label sets, however, procuring an adequate volume of medical imaging data for training is a formidable task. Various data augmentation strategies can mitigate the underfitting issue inherent in supervised learning-based models that are trained on limited medical image and label sets. This research investigates the enhancement of a deep learning-based rib fracture segmentation model and the efficacy of data augmentation techniques such as left-right flipping, rotation, and scaling. Augmented dataset with L/R flipping and rotations(30°, 60°) increased model performance, however, dataset with rotation(90°) and ⨯0.5 rescaling decreased model performance. This indicates the usage of appropriate data augmentation methods depending on datasets and tasks.

• Journal of the Health Care and Life Science
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• v.10 no.2
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• pp.413-421
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• 2022

The online questionnaire platform was conducted with Korean medicine doctors to analyses the recognition of applicability of artificial intelligence(AI) to the field of application and department of Korean medicine. Most of all respondents did not have a chance to participate academic experience or research experience related to AI, but had a high willingness to participate in further learning and research. The level of AI understanding was supervised learning When AI is introduced to Korean medicine, the mean predicted usefulness scores to each application field for research and development of oriental medicine(74.60 points) and social policy establishment(73.68 points) are significantly higher than other of Korean medicine field of application, while those of Sasang constitutional department(66.61 points) and Korean medicine rehabilitation(65.91 points) were evaluated higher than other fields of treatment of Korean medicine. Respondents judged that the introduction of AI could be realistically useful in relatively formal fields of Korean medicine, while it would be difficult in non-formal fields.

• Journal of the Korea Convergence Society
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• v.8 no.10
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• pp.9-17
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• 2017

The current study attempted to develop and operate an exercise prescription expert system based on cloud computing. Recently, concerns on health are increasing due to the development of healthcare technology, increased life expectancy, and enhanced concerns on the body figure and wellbeing among Koreans. This trend pushes up the demand for the personal trainers and exercise specialists. However, supply of the exercise specialists are less than the demand. This study tries to develop exercise prescription system, aggregate diverse data, develop artificial intelligence rule, and operate exercise prescription expert system and education system. This system may assist training exercise professionals by replacing off-line training programs into on-line training programs. Further researches are recommended to connect diverse IoT devices and big data.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.1-9
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• 2022

In this paper, we propose the Deep Learning-Based Companion Animal Abnormal Behavior Detection Service, which using video and sensor data. Due to the recent increase in households with companion animals, the pet tech industry with artificial intelligence is growing in the existing food and medical-oriented companion animal market. In this study, companion animal behavior was classified and abnormal behavior was detected based on a deep learning model using various data for health management of companion animals through artificial intelligence. Video data and sensor data of companion animals are collected using CCTV and the manufactured pet wearable device, and used as input data for the model. Image data was processed by combining the YOLO(You Only Look Once) model and DeepLabCut for extracting joint coordinates to detect companion animal objects for behavior classification. Also, in order to process sensor data, GAT(Graph Attention Network), which can identify the correlation and characteristics of each sensor, was used.

• Smart Media Journal
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• v.12 no.2
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• pp.42-55
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• 2023

The combination of blockchain (BC), artificial Intelligence (AI), quantum computing (QC), and the Internet of Things (IoT) can potentially transform various industries and domains, including healthcare, logistics, and finance. In this paper, we look at the trends and developments in integrating these emerging technologies and the potential benefits and challenges that come with them. We present a conceptual framework for integrating BC, AI, QC, and IoT and discuss the framework's key characteristics and challenges. We also look at the most recent cutting-edge research and developments in integrating these technologies, as well as the key challenges and opportunities that come with them. Our analysis highlights the potential benefits of integrating the technologies and looks to increased security, privacy, and efficiency to provide insights into the future of these technologies.