• Journal of dental hygiene science
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• v.20 no.1
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• pp.16-24
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• 2020

Background: Dental treatment has shifted to the center of the community, and the public policy of the country has expanded to support the vulnerable classes such as the disabled. The dental profession needs education regarding oral health services for persons with disabilities, and it is necessary to derive the competencies for this. Therefore, we conducted this study to derive the normative ability to understand the role of a dental hygienist in the oral health service for persons with disabilities and improvement plans for education. Methods: We conducted a qualitative analysis for deriving competencies by analyzing the data collected through in-depth interviews with experts in order to obtain abilities through practical experience. Based on the competency criterion, relevant competency in the interview response was derived using the priori method, and it was confirmed whether the derived ability matched the ability determined by the respondent. Results: The professional conduct competencies of dental hygienists, devised by the Korean Association of Dental Hygiene, consists of professional behavior, ethical decision-making, self-assessment skills, lifelong learning, and accumulated evidence. Also, core competencies of the American Dental Education Association competencies for dental hygienist classification such as ethics, responsibility for professional actions, and critical thinking skills were used as the criterion. The dental hygienist's abilities needed for oral health care for people with disabilities, especially in the detailed abilities to fulfill these social needs, were clarified. Conclusion: To activate oral health care for people with disabilities, it is necessary for dental hygienists to fulfill their appropriate roles, and for this purpose, competency-based curriculum restructuring is indispensable. A social safety net for improving the oral health of people with disabilities can be secured by improving the required skills-based education system of dental hygienists and strengthening the related infrastructure.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.365-372
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• 2021

The purpose of this study was to examine the statements characteristics of the pressure ulcer nursing record by natural langage processing and assess the prediction accuracy for each pressure ulcer stage. Nursing records related to pressure ulcer were analyzed using descriptive statistics, and word cloud generators (http://wordcloud.kr) were used to examine the characteristics of words in the pressure ulcer prevention nursing records. The accuracy ratio for the pressure ulcer stage was calculated using deep learning. As a result of the study, the second stage and the deep tissue injury suspected were 23.1% and 23.0%, respectively, and the most frequent key words were erythema, blisters, bark, area, and size. The stages with high prediction accuracy were in the order of stage 0, deep tissue injury suspected, and stage 2. These results suggest that it can be developed as a clinical decision support system available to practice for nurses at the pressure ulcer prevention care.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.10
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• pp.239-246
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• 2020

In the medical field where artificial intelligence technology is introduced, research related to clinical decision support system(CDSS) in relation to diagnosis and prediction is actively being conducted. In particular, medical imaging-based disease diagnosis area applied AI technologies at various products. However, medical imaging data consists of inconsistent data, and it is a reality that it takes considerable time to prepare and use it for research. This paper describes a one-stop AI learning platform for converting to medical image standard R_CDM(Radiology Common Data Model) and supporting AI algorithm development research based on the dataset. To this, the focus is on linking with the existing CDM(common data model) and model the system, including the schema of the medical imaging standard model and report information for multi-center research based on DICOM(Digital Imaging and Communications in Medicine) tag information. And also, we show the execution results based on generated datasets through the AI learning platform. As a proposed platform, it is expected to be used for various image-based artificial intelligence researches.

• Journal of Biomedical Engineering Research
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• v.19 no.5
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• pp.469-476
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• 1998

In the case of acquisition and displaying medical Images such as ultrasonography and endoscopy on VGA monitor of PC system, image degradation of tear-drop appears through scan conversion. In this study, we compare several methods which can solve this degradation and implement the hardware system that resolves this problem in real-time with PC. It is possible to represent high quality image display and real-time processing and acquisition with specific de-interlacing device and PCI bridge on our hardware system. Image quality is improved remarkably on our hardware system. It is implemented as PC-based system, so acquiring, saving images and describing text comment on those images and PACS networking can be easily implemented.metabolism. All images were spatially normalized to MNI standard PET template and smoothed with 16mm FWHM Gaussian kernel using SPM96. Mean count in cerebral region was normalized. The VOls for 34 cerebral regions were previously defined on the standard template and 17 different counts of mirrored regions to hemispheric midline were extracted from spatially normalized images. A three-layer feed-forward error back-propagation neural network classifier with 7 input nodes and 3 output nodes was used. The network was trained to interpret metabolic patterns and produce identical diagnoses with those of expert viewers. The performance of the neural network was optimized by testing with 5~40 nodes in hidden layer. Randomly selected 40 images from each group were used to train the network and the remainders were used to test the learned network. The optimized neural network gave a maximum agreement rate of 80.3% with expert viewers. It used 20 hidden nodes and was trained for 1508 epochs. Also, neural network gave agreement rates of 75~80% with 10 or 30 nodes in hidden layer. We conclude that artificial neural network performed as well as human experts and could be potentially useful as clinical decision support tool for the localization of epileptogenic zones.

• Journal of Industrial Convergence
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• v.20 no.10
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• pp.51-59
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• 2022

This study aims to investigate the changes in health status of inpatients before and after a fall accident, and it is a retrospective study using data from 328 inpatients who fell from January 1, 2016 to December 31, 2020, reported to the patient safety reporting system. The average age of the study subjects was 68.57(±14.13), and those in their 70s accounted for the most at 30.49%. Falls occurred on average 13.86(±25.03) days after hospitalization, and the time when the most falls occurred was between 22:30 and 06:59 with 42.99%. Before and after a fall during hospitalization, bowel problems (x²=314.0, p<.001), urination problems (x²=284.0, p<.001), intravenous fluid therapy (x²=85.16, p<.001), and walking (x²=69.77. p<.001), bedridden state (x²=51.60, p< .001), mental state and performance (x²=17.52, p<.001) patient's attitude (x²=220.17, p<.001), there was a statistically significant difference. It is necessary to develop an appropriate method and education program for fall prevention in hospital by considering the individual characteristics of inpatient.

• The Korean Society of Law and Medicine
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• v.24 no.2
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• pp.147-196
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• 2023

Advances in brain science have made it possible to stimulate the brain to treat brain disorder or to connect directly between the neuron activity and an external devices. Non-invasive neurotechnologies already exist, but invasive neurotechnologies can provide more precise stimulation or measure brainwaves more precisely. Nowadays deep brain stimulation (DBS) is recognized as an accepted treatment for Parkinson's disease and essential tremor. In addition DBS has shown a certain positive effect in patients with Alzheimer's disease and depression. Brain-computer interfaces (BCI) are in the clinical stage but help patients in vegetative state can communicate or support rehabilitation for nerve-damaged people. The issue is that the people who need these invasive neurotechnologies are those whose capacity to consent is impaired or who are unable to communicate due to disease or nerve damage, while DBS and BCI operations are highly invasive and require informed consent of patients. Especially in areas where neurotechnology is still in clinical trials, the risks are greater and the benefits are uncertain, so more explanation should be provided to let patients make an informed decision. If the patient is under guardianship, the guardian is able to substitute for the patient's consent, if necessary with the authorization of court. If the patient is not under guardianship and the patient's capacity to consent is impaired or he is unable to express the consent, korean healthcare institution tend to rely on the patient's near relative guardian(de facto guardian) to give consent. But the concept of a de facto guardian is not provided by our civil law system. In the long run, it would be more appropriate to provide that a patient's spouse or next of kin may be authorized to give consent for the patient, if he or she is neither under guardianship nor appointed enduring power of attorney. If the patient was not properly informed of the risks involved in the neurosurgery, he or she may be entitled to compensation of intangible damages. If there is a causal relation between the malpractice and the side effects, the patient may also be able to recover damages for those side effects. In addition, both BCI and DBS involve the implantation of electrodes or microchips in the brain, which are controlled by an external devices. Since implantable medical devices are subject to product liability laws, the patient may be able to sue the manufacturer for damages if the defect caused the adverse effects. Recently, Korea's medical device regulation mandated liability insurance system for implantable medical devices to strengthen consumer protection.