• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.939-945
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• 2023

This study analyzes the 'performance efficiency' of AI-based reading assistance systems in the field of radiology by measuring their 'time behavior' properties. Due to the increase in medical images and the limited number of radiologists, the adoption of AI-based solutions is escalating, stimulating a multitude of studies in this area. Contrary to the majority of past research which centered on AI's diagnostic precision, this study underlines the significance of time behavior. Using 50 chest X-ray PA images, the system processed images in an average of 15.24 seconds, demonstrating high consistency and reliability, which is on par with leading global AI platforms, suggesting the potential for significant improvements in radiology workflow efficiency. We expect AI technology to play a large role in the field of radiology and help improve overall healthcare quality and efficiency.

• Journal of Biomedical Engineering Research
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• v.44 no.6
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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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• v.21 no.3
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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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• v.18 no.2
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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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• v.23 no.12
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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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• v.24 no.3
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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

• Journal of Korean Academy of Nursing
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• v.54 no.2
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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.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.43-54
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• 2024

Recently, there has been a lot of research on utilizing Language Models, and Large Language Models have achieved innovative results in various tasks. However, the practical application faces limitations due to the constrained resources and costs required to utilize Large Language Models. Consequently, there has been recent attention towards methods to effectively utilize models within given resources. Curriculum Learning, a methodology that categorizes training data according to difficulty and learns sequentially, has been attracting attention, but it has the limitation that the method of measuring difficulty is complex or not universal. Therefore, in this study, we propose a methodology based on data heterogeneity-based Curriculum Learning that measures the difficulty of data using reliable prior information and facilitates easy utilization across various tasks. To evaluate the performance of the proposed methodology, experiments were conducted using 5,000 specialized documents in the field of information communication technology and 4,917 documents in the field of healthcare. The results confirm that the proposed methodology outperforms traditional fine-tuning in terms of classification accuracy in both LoRA fine-tuning and full fine-tuning.

• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1000-1007
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• 2011

Home Networking will be implementing the interactive network by home appliances over wireless/wireline network framwork. That is, Home appliances, which are being operated within home space configure the network through wireline/wireless network infrastructure for interworking and interacitive services by external internet access. Based on home networking, smarthome is home space where can use automatic telecommunication and interactive service by home appliances. we can call smarthome based on home networking infrastructure as the conceptual gateway for evolving future converged space like u-city. From simple home control service to home automation service over home networking infrastructure, smarthome service is evolving to up-to-date intelligent life environment in growth of IT technology. however, its service model development was based on supplier-centered based on advanced IT technology. because of this situation, smarthome service has not been acknowledged IT underprivileged people as well as IT early-adaptor. so, this research paper will consider and try to find out what will be the feasible factors to make the best service for IT underprivileged people.

• Journal of radiological science and technology
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• v.44 no.5
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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.