• 한국방사선학회논문지
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• 제17권6호
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• pp.939-945
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• 2023

본 연구는 영상의학 분야에서 인공지능(AI) 기술 기반의 판독 보조 시스템의 'Time Behavior(시간반응성)' 속성을 측정하여 '성능 효율성'을 분석하였다. 의료 영상의 증가와 영상의학 전문의 수의 한계로 인해 인공지능(AI) 기술 기반의 솔루션이 증가하고 있으며, 관련된 연구가 많이 수행되고 있다. 하지만 대부분의 선행 연구가 인공지능의 진단 정확도에 초점을 맞췄다면, 본 연구는 Time Behavior의 중요성을 강조하여 수행하였다. 50개의 흉부 엑스레이 PA 이미지를 사용하여 측정한 결과, 평균 15.24초 만에 영상을 처리하여 높은 일관성과 안정성을 보여주었고, 이 처리 속도는 유명 글로벌 AI 플랫폼과 동등한 수준으로 영상의학과 워크플로우 효율성 부분에 크게 개선될 수 있는 가능성을 제시하였다. 앞으로 인공지능 기술이 영상의학 분야에서 큰 역할을 담당하여, 전반적인 의료 품질 향상과 효율성을 개선하는 데 도움이 될 것으로 기대한다.

• 대한의용생체공학회:의공학회지
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• 제44권6호
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• pp.428-442
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• 2023

In this study, we have a goal to develop usability evaluation guidelines for heuristic-based artificial intelligence-based Software as a Medical Device (SaMD) in the medical field. We conducted a gap analysis between medical hardware (H/W) and non-medical software (S/W) based on ten heuristic principles. Through severity assessments, we identified 69 evaluation domains and 112 evaluation criteria aligned with the ten heuristic principles. Subsequently, we categorized each evaluation domain into five types, including user safety, data integrity, regulatory compliance, patient therapeutic effectiveness, and user convenience. We proposed usability evaluation guidelines that apply the newly derived heuristic-based Software as a Medical Device (SaMD) evaluation factors to the risk management process. In the discussion, we also have proposed the potential applications of the research findings and directions for future research. We have emphasized the importance of the judicious application of AI technology in the medical field and the evaluation of usability evaluation and offered valuable guidelines for various stakeholders, including medical device manufacturers, healthcare professionals, and regulatory authorities.

• Genomics & Informatics
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• 제21권3호
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• pp.34.1-34.10
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• 2023

Nosocomial infections, commonly referred to as healthcare-associated infections, are illnesses that patients get while hospitalized and are typically either not yet manifest or may develop. One of the most prevalent nosocomial diseases in hospitalized patients is pneumonia, among the leading causes of mortality and morbidity. Viral, bacterial, and fungal pathogens cause pneumonia. More severe introductions commonly included Staphylococcus aureus, which is at the top of bacterial infections, per World Health Organization reports. The staphylococci, S. aureus, strain RMI-014804, mesophile, on-sporulating, and non-motile bacterium, was isolated from the sputum of a pulmonary patient in Pakistan. Many characteristics of S. aureus strain RMI-014804 have been revealed in this paper, with complete genome sequence and annotation. Our findings indicate that the genome is a single circular 2.82 Mbp long genome with 1,962 protein-coding genes, 15 rRNA, 49 tRNA, 62 pseudogenes, and a GC content of 28.76%. As a result of this genome sequencing analysis, researchers will fully understand the genetic and molecular basis of the virulence of the S. aureus bacteria, which could help prevent the spread of nosocomial infections like pneumonia. Genome analysis of this strain was necessary to identify the specific genes and molecular mechanisms that contribute to its pathogenicity, antibiotic resistance, and genetic diversity, allowing for a more in-depth investigation of its pathogenesis to develop new treatments and preventive measures against infections caused by this bacterium.

• Nutrition Research and Practice
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• 제18권2호
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• pp.294-307
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• 2024

BACKGROUND/OBJECTIVES: Dietitians frequently use nutrition education tools to facilitate dietary counselling sessions. Nevertheless, these tools may require adaptation to keep pace with technological advancements. This study had a 2-fold purpose: first, to identify the types of nutrition education tools currently in use, identify their limitations, and explore dietitians' perspectives on the importance of these tools; second, to investigate the features that dietitians prefer in digital nutrition education tools. SUBJECTS/METHODS: A semi-structured face-to-face interview was conducted among 15 dietitians from selected public hospitals, primary care clinics, and teaching hospitals in Malaysia. Inductive thematic analysis of the responses was conducted using NVivo version 12 software. RESULTS: Most dietitians used physical education tools including the healthy plate model, pamphlets, food models, and flip charts. These tools were perceived as important as they facilitate the nutrition assessment process, deliver nutrition intervention, and are time efficient. However, dietitians described the current educational tools as impersonal, outdated, limited in availability due to financial constraints, unhandy, and difficult to visualise. Alternatively, they strongly favoured digital education tools that provided instant feedback, utilised an automated system, included a local food database, were user-friendly, developed by experts in the field, and seamlessly integrated into the healthcare system. CONCLUSION: Presently, although dietitians have a preference for digital educational tools, they heavily rely on physical nutrition education tools due to their availability despite the perception that these tools are outdated, impersonal, and inconvenient. Transitioning to digital dietary education tools could potentially address these issues.

• International Journal of Computer Science & Network Security
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• 제23권12호
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• pp.167-174
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• 2023

Electronic educational environments in the conditions of quarantine restrictions of COVID-19 have become a common phenomenon for the organization of distance educational activities. Under the conditions of Russian aggression, Ukrainian proof of their use is unique. The purpose of the article is to analyze the role of electronic educational environments in the process of training applicants for higher education in Ukraine in the realities of a large-scale war. General scientific methods (analysis, synthesis, deduction, and induction) and special pedagogical prognostic methods, modeling, and SWOT analysis methods were used. In the results, the general properties of the Internet educational platforms common in Ukraine, the peculiarities of using the Moodle and Prometheus platforms, and an approximate model of the electronic learning environment were discussed. The reasons for the popularity of Moodle among Ukrainian universities are analyzed, but vulnerable elements related to security are emphasized. It was also determined that the high cost of Prometheus software and less functionality made this learning environment less relevant. The conclusions state that the military actions drew the attention of universities in Ukraine to the formation of their own educational platforms. This is especially relevant for technical and military institutions of higher education.

• International Journal of Computer Science & Network Security
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• 제24권3호
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• pp.59-70
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• 2024

Background: The COVID-19 pandemic (the form of coronaviruses) developed at the end of 2019 and spread rapidly to almost every corner of the world. It has infected around 25,334,339 of the world population by the end of September 1, 2020 [1] . It has been spreading ever since, and the peak specific to every country has been rising and falling and does not seem to be over yet. Currently, the conventional RT-PCR testing is required to detect COVID-19, but the alternative method for data archiving purposes is certainly another choice for public departments to make. Researchers are trying to use medical images such as X-ray and Computed Tomography (CT) to easily diagnose the virus with the aid of Artificial Intelligence (AI)-based software. Method: This review paper provides an investigation of a newly emerging machine-learning method used to detect COVID-19 from X-ray images instead of using other methods of tests performed by medical experts. The facilities of computer vision enable us to develop an automated model that has clinical abilities of early detection of the disease. We have explored the researchers' focus on the modalities, images of datasets for use by the machine learning methods, and output metrics used to test the research in this field. Finally, the paper concludes by referring to the key problems posed by identifying COVID-19 using machine learning and future work studies. Result: This review's findings can be useful for public and private sectors to utilize the X-ray images and deployment of resources before the pandemic can reach its peaks, enabling the healthcare system with cushion time to bear the impact of the unfavorable circumstances of the pandemic is sure to cause

• 대한간호학회지
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• 제54권2호
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• pp.193-210
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• 2024

Purpose: The objective of this study was to develop a predictive model for the sexual experiences of adolescents using the random forest method and to identify the "variable importance." Methods: The study utilized data from the 2019 to 2021 Korea Youth Risk Behavior Web-based Survey, which included 86,595 man and 80,504 woman participants. The number of independent variables stood at 44. SPSS was used to conduct Rao-Scott χ² tests and complex sample t-tests. Modeling was performed using the random forest algorithm in Python. Performance evaluation of each model included assessments of precision, recall, F1-score, receiver operating characteristics curve, and area under the curve calculations derived from the confusion matrix. Results: The prevalence of sexual experiences initially decreased during the COVID-19 pandemic, but later increased. "Variable importance" for predicting sexual experiences, ranked in the top six, included week and weekday sedentary time and internet usage time, followed by ease of cigarette purchase, age at first alcohol consumption, smoking initiation, breakfast consumption, and difficulty purchasing alcohol. Conclusion: Education and support programs for promoting adolescent sexual health, based on the top-ranking important variables, should be integrated with health behavior intervention programs addressing internet usage, smoking, and alcohol consumption. We recommend active utilization of the random forest analysis method to develop high-performance predictive models for effective disease prevention, treatment, and nursing care.

• 한국컴퓨터정보학회논문지
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• 제29권3호
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• pp.43-54
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• 2024

최근 언어모델을 활용하기 위한 연구가 활발히 이루어지며, 큰 규모의 언어모델이 다양한 과제에서 혁신적인 성과를 달성하고 있다. 하지만 실제 현장은 거대 언어모델 활용에 필요한 자원과 비용이 한정적이라는 한계를 접하면서, 최근에는 주어진 자원 내에서 모델을 효과적으로 활용할 수 있는 방법에 주목하고 있다. 대표적으로 학습 데이터를 난이도에 따라 구분한 뒤 순차적으로 학습하는 방법론인 커리큘럼 러닝이 주목받고 있지만, 난이도를 측정하는 방법이 복잡하거나 범용적이지 않다는 한계를 지닌다. 따라서, 본 연구에서는 신뢰할 수 있는 사전 정보를 통해 데이터의 학습 난이도를 측정하고, 이를 다양한 과제에 쉽게 활용할 수 있는 데이터 이질성 기반 커리큘럼 러닝 방법론을 제안한다. 제안방법론의 성능 평가를 위해 국가 R&D 과제 전문 문서 중 정보통신 분야 전문 문서 5,000건, 보건의료전문 문서 데이터 4,917건을 적용하여 실험을 수행한 결과, 제안 방법론이 LoRA 미세조정과 전체 미세조정 모두에서 전통적인 미세조정에 비해 분류 정확도 측면에서 우수한 성능을 나타냄을 확인했다.

• 한국항행학회논문지
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• 제15권6호
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• pp.1000-1007
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• 2011

홈 네트워킹(Home Networking)이란 유무선 네트워크 기반 하에서 가정 내 정보기기에 의한 상호 네트워크를 구축하는 것이라 할 수 있다. 다시 말해서 홈이라는 공간적 틀 안에서 이용되어지는 정보가전 기기들이 유무선 네트워크를 통해 서로 네트워크를 구성하여 상호 접속하게 하고 외부의 인터넷 엑세스에 대해서 상호 허용하고 통신하는 환경을 구축하는 것을 의미한다고 할 수 있다. 이를 기반으로 스마트 홈이라 함은 홈네트워킹기반의 가정환경에서 인간으로 하여금 자동화된 통신서비스를 사용할 수 있게 하는 주택이라고 할 수 있다. 이러한, 홈네트워킹 기반의 스마트 홈은 u-city와 같은 미래 converged 주거공간에 대한 개념적 게이트웨이라고 할 수 있을 것이다. 단순한 기능의 댁내 홈서비스 제어 환경이 홈오토메이션형태로 진화하고 현재와 같이 통신 네트워크 환경 기반의 최첨단을 확보한 인텔리전트 생활환경에서의 스마트홈네트워크 서비스는 IT의 발달에 따른 일반화된 서비스의 형상으로 우리의 삶에 공존하고 있다. 그러나 기술진화의 빠른 속도에 따른 공급자 위주의 서비스출시는 IT서비스 소외계층은 물론, 소위, early-adaptor라 하는 IT 선도계층에 까지 그 기술의 우수성과 선행성에도 불구하고 일정 부분 그 가치를 인정받지 못하고 있는 것이 현실이다. 이에 본 논문은 첨단 스마트홈서비스의 바람직한 요구 및 기대사항에 대해서 고민하여 바람직한 IT소외계층을 목표로 한 서비스 모델에 대해 논하고자 한다.

• 대한방사선기술학회지:방사선기술과학
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• 제44권5호
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• pp.513-523
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• 2021

The purpose of this study was to discuss the required items and feasibility of medical records of radiological examinations performed by radiological technologists at medical institutions. An online survey was conducted to a total of 10,000 radiation-related workers, of which 1,026 (10.3%) responded. As a research method, self-made questionnaires were used. The online survey was conducted from September 10 to September 20, 2021 for the survey period. For response data, a Chi-square test was performed according to demographic characteristics using SPSS 27.0 version (IBM Inc., Chicago, Ill, USA), and it was judged to be significant when the P value was less than 0.05. The reliability of the questionnaire response was found to be Chronbach α=0.933. More than 90% of the medical records related to radiological examinations are necessary, and they answered that a curriculum, remuneration curriculum, and legal system for medical records should be prepared. More than 90% of the respondents agreed with the proposal of the Radiological Technologist Independent Act for legal preparation, and most of the information required for medical records is currently recorded in DICOM images. According to the demographic characteristics, the medical record requirement for radiological examination, curriculum, continuing education, and legislation were found to be higher with higher education and higher with longer working experience. In addition, most of the radiology departments showed a high demand for medical records, so most of them responded positively to the medical records requirements for radiological examinations. This study analyzed the medical record requirements for radiological examinations, and as shown in the results, medical record requirements for radiological examinations was found that most radiological technologists felt need for the new law and supported it. In addition, if the information recorded in the DICOM image is used, it is considered that medical records could be easily prepared without additional work by the radiological technologists.