• Clinical and Experimental Pediatrics
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• v.61 no.1
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• pp.30-34
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• 2018

Congenital pulmonary airway malformation (CPAM), previously known as congenital cystic adenomatoid malformation, is a rare developmental lung abnormality associated with rhabdomyosarcoma, pleuropulmonary blastoma, and mucinous adenocarcinoma of the lung. We report an unusual case of a 10-day-old male newborn with a left lower lobe pulmonary cyst who underwent lobectomy, which revealed type II CPAM complicated by multifocal mucinous adenocarcinoma. KRAS sequencing revealed a somatic mutation in Codon12 ($GGT{\rightarrow}GAT$), suggesting the development of a mucinous adenocarcinoma in the background of mucinous metaplasia. Mucinous adenocarcinoma is the most common lung tumor associated with CPAM, but it generally occurs in older children and adults. Further, all cases in the literature are of type I CPAM. This case in a neonate indicates that malignant transformation can occur very early in type II CPAM.

• Journal of Biomedical Engineering Research
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• v.42 no.6
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• pp.277-286
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• 2021

The global market size of AI based SaMD for medical image in 2023 will be anticipated to reach around 620 billion won (518 million dollars). In order for Korean manufacturers to efficiently obtain CE marking for marketing in the EU countries, the paper is to introduce the recommendation and suggestion of how to reclassify SaMD based on classification rules of MDR because, after introducing the Regulation EU 2017/745, classification rules are quite modified and newly added compared to the Directive 93/42/EEC. In addition, the paper is to provide several rules of MDR that may be applicable to decide the classification of SaMD. Lastly, the paper is to examine and demonstrate various secondary data supported by qualitative data because the paper focuses on the suggestion and recommendation with a public trust on the basis of various secondary data conducted by the analysis of field data. In conclusion, the paper found that the previous classification of SaMD followed by the rule of MDD should be reclassified based on the Regulation EU 2017/745. Therefore, the suggestion and recommendation are useful for Korean manufacturers to comprehend the classification of SaMD for marketing in the EU countries.

• Journal of Radiation Protection and Research
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• v.47 no.3
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• pp.111-133
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• 2022

The exciting advancement related to the "modeling of digital human" in terms of a computational phantom for radiation dose calculations has to do with the latest hype related to deep learning. The advent of deep learning or artificial intelligence (AI) technology involving convolutional neural networks has brought an unprecedented level of innovation to the field of organ segmentation. In addition, graphics processing units (GPUs) are utilized as boosters for both real-time Monte Carlo simulations and AI-based image segmentation applications. These advancements provide the feasibility of creating three-dimensional (3D) geometric details of the human anatomy from tomographic imaging and performing Monte Carlo radiation transport simulations using increasingly fast and inexpensive computers. This review first introduces the history of three types of computational human phantoms: stylized medical internal radiation dosimetry (MIRD) phantoms, voxelized tomographic phantoms, and boundary representation (BREP) deformable phantoms. Then, the development of a person-specific phantom is demonstrated by introducing AI-based organ autosegmentation technology. Next, a new development in GPU-based Monte Carlo radiation dose calculations is introduced. Examples of applying computational phantoms and a new Monte Carlo code named ARCHER (Accelerated Radiation-transport Computations in Heterogeneous EnviRonments) to problems in radiation protection, imaging, and radiotherapy are presented from research projects performed by students at the Rensselaer Polytechnic Institute (RPI) and University of Science and Technology of China (USTC). Finally, this review discusses challenges and future research opportunities. We found that, owing to the latest computer hardware and AI technology, computational human body models are moving closer to real human anatomy structures for accurate radiation dose calculations.

• Journal of the Korean Society of Radiology
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• v.83 no.4
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• pp.759-770
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• 2022

The importance of ethics in research and the use of artificial intelligence (AI) is increasingly recognized not only in the field of healthcare but throughout society. This article intends to provide domestic readers with practical points regarding the ethical issues of using radiological images for AI research, focusing on data security and privacy protection and the right to data. Therefore, this article refers to related domestic laws and government policies. Data security and privacy protection is a key ethical principle for AI, in which proper de-identification of data is crucial. Sharing healthcare data to develop AI in a way that minimizes business interests is another ethical point to be highlighted. The need for data sharing makes the data security and privacy protection even more important as data sharing increases the risk of data breach.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.4
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• pp.701-708
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• 2024

The advent of transformer architectures in deep learning has been a major breakthrough in natural language processing research. Object name recognition is a branch of natural language processing and is an important research area for tasks such as information retrieval. It is also important in the biomedical field, but the lack of Korean biomedical corpora for training has limited the development of Korean clinical research using AI. In this study, we built a new biomedical corpus for Korean biomedical entity name recognition and selected language models pre-trained on a large Korean corpus for transfer learning. We compared the name recognition performance of the selected language models by F1-score and the recognition rate by tag, and analyzed the errors. In terms of recognition performance, KlueRoBERTa showed relatively good performance. The error analysis of the tagging process shows that the recognition performance of Disease is excellent, but Body and Treatment are relatively low. This is due to over-segmentation and under-segmentation that fails to properly categorize entity names based on context, and it will be necessary to build a more precise morphological analyzer and a rich lexicon to compensate for the incorrect tagging.

• Journal of Society of Preventive Korean Medicine
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• v.28 no.1
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• pp.31-42
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• 2024

Objective : In order to understand the changes in domestic approval regulations applicable to traditional Korean medical device companies, this article will explain the major amendments 「Regulation on Medical Device Approval Report Review, etc.」 from 2005 to the present on a year-by-year basis, and provide a counter plan to the recent changes in approval regulations. Methods : We analysed the changes in approval regulatory amendments related to the traditional Korean medical devices from 2005 to the present. Results : The Ministry of Food and Drug Safety is continuously improving medical device approval regulations to ensure the global competitiveness of domestic medical devices and contribute to the improvement of public health. Recent major approval regulatory amendments include the establishment of a review system for software medical devices and digital therapeutics, the recognition of real world evidence materials, the introduction of a biological evaluation of medical devices within a risk management process and a medical device approval licence renewal system. Conclusions : It is expected that the range of medical devices available to Korean medicine doctors will continue to expand in the future through the provision of non-face-to-face medical services and the development of advanced and new medical devices, as well as wearable medical devices and digital therapeutics. In order to increase the market entry potential of traditional Korean medical devices that incorporate advanced technologies such as digital technology and AI-based diagnosis and prediction technology, it is urgent that the government provide significant support to traditional Korean medical device companies to improve approval regulatory compliance.

• Journal of agricultural medicine and community health
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• v.34 no.1
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• pp.58-66
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• 2009

Objectives: Active participation of poultry breeder in surveillance system of Avian Influenza (AI) is very important. Therefore this study was conducted to present basis data for active report of AI that is affected by media's coverage in poultry breeder. Methods: Subjects were 88 persons, 28 who were poultry breeder at epidemic area of AI and 60 who were general person at non-epidemic area. Data were collected by the trained investigator from Jul. 1 to Aug. 31, 2008. Respondents were interviewed by means of a structured questionnaire. Results: The third-person effect among perceptions of influence in media's report on the AI was higher in breeder (32.1%) than in non-breeder (10.0%). However, Confidence to media report on the AI was lower in breeder than in non-breeder. Intention to report of the AI was 71.4% in breeder respectively, was 90.0% in non-breeder. There was statistically significant lower in breeder than non-breeder. The cause of avoidance of report was 'economic damage' for 87.5%, which acocounted for the majority of cases. Confidence to media report on the AI were positively correlated with concern on the AI and perception on seriousness of the AI, but negatively correlated with the third-person effect. Conclusions: These results showed that intention to report of the AI of breeder was susceptible to influenced by the third person effect and confidence in media's report on the AI. Therefore we should give a special attention to increase active report of poultry breeder during epidemic period of AI which is consideration of reasonable strategy of media's coverage, including mind and emotion state of poultry breeder.

• Clinical and Experimental Pediatrics
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• v.46 no.4
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• pp.389-392
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• 2003

Netherton's syndrome is an unusual disorder which consists of triad of ichtyosiform dermatosis, multiple defects of hair shaft and an atopic diathesis. The finding of bamboo hair is pathognomic in Netherton's syndrome and the ichthyosiform dermatosis may consist of either ichtyosis linearis circumflexa or congenital ichthyosiform erythroderma. Often, variability in the clinical features leads to a delay in diagnosis in many cases. We report a case of Netherton's syndrome diagnosed in the neonatal period. The patient presented with severe ichthyosis and confirmed microscopically distinctive bamboo hair.

• The International Journal of Costume Culture
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• v.8 no.2
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• pp.124-131
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• 2005

This study focused on the change of skin temperature by the emissivity and emission power of far-infrared for conformant far infrared effect to naked eyes. The study method is to manufacture the bra pad by each concentration on far-infrared materials of illite powder $(K,H_3O)AI_2(Si,Al)_4O_{10}(H_2O,OH)_2)$, liquid alumina ($Al_2O_3$), the extracted liquid from 29 kind of medical plants, then, measured change of skin temperature. Result are as follows. Far-infrared were emitted each $90.2\%,\;90.1\%,\;89.7\%$ from the illite powder, liquid alumina, extracted liquid from medical plants. When the testee weared the bra pad, the temperature of coated bra pad was $0.5^{\circ}C$ higher than the non finished bra pad. Washing fastness on far-infrared finishing was better dope addition method than coating method.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_2
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• pp.1083-1090
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• 2022

Since renal cell carcinoma(RCC) has various examination and treatment methods according to clinical stage and histopathological characteristics, it is required to determine accurate and efficient treatment methods in the clinical field. However, the process of collecting and processing RCC medical data is difficult and complex, so there is currently no AI-based clinical decision support system for RCC treatments worldwide. In this study, we propose a clinical decision support system that helps clinicians decide on a precision treatment to each patient. RCC standard big database is built by collecting structured and unstructured data from the standard common data model and electronic medical information system. Based on this, various machine learning classification algorithms are applied to support a better clinical decision making.