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Skill training in nursing education has been highly dependent on self-training because of Korea's high student-faculty ratio. Students tend to have a passive attitude in self-practice, and it is hard to expect effective learning outcomes with traditional checklist-dependent self-practice. Smart glasses have a high potential to assist nursing students with timely information, and a hands-free device does not interrupt performance. This study aimed to develop a smart glass-based nursing skill training program and evaluate its usability and feasibility for the implementation of self-practice. We conducted a usability and feasibility study with 30 undergraduate nursing students during a 2-hour open lab for self-practice of core nursing skills, wearing smart glasses for visualized guidance. The usability test was conducted using a 16-item self-reporting questionnaire and 7 open-ended questions. Learning satisfaction was assessed using a 7-item questionnaire. The number of practice sessions was recorded, and perceived competency in core nursing skills was measured before and after the intervention. At the final evaluation, performance accuracy and time consumed for completion were recorded. Smart glass-assisted self-practice of nursing skills was perceived as helpful, convenient, and interesting. Participants reported improved recollection of sequences of skills, and perceived competency was significantly improved. Several issues were raised by participants regarding smart glasses, including small screen size, touch sensors, fogged lenses with masks, heaviness, and heat after a period of time. Smart glasses have the potential to assist self-practice, providing timely information at students' own paces. Having both hands free from holding a device, participants reported the convenience of learning as they could practice and view the information simultaneously. Further revision correcting reported issues would improve the applicability of smart glasses in other areas of nursing education.

Schizophrenia is one of the most prevalent mental illnesses contributing to national burden worldwide. It is well known that mental health nursing education, including clinical placement, is still insufficient to reach the optimal level of competency in nursing students. This study suggests a new form of mental health virtual reality (VR) simulation that is user-friendly and engaging to improve education about schizophrenia, thereby improving its treatment. A mixed-methods study was conducted with a total of 60 nursing students, using 360-degree videos of five different scenarios reflecting clinical symptoms of schizophrenia patients and related treatment tasks delivered via head-mounted displays (HMDs). We used a 17-item quantitative questionnaire and a 7-item open-ended qualitative questionnaire to evaluate the ease of use and usefulness of the VR simulation program and to identify areas where further improvement is required. The VR simulation program was perceived as useful and exciting. Participants stressed that the high realism of the simulation increased their engagement in and motivation to learn about mental health nursing. Some participants made suggestions, such as further refining the picture and sound quality in order to achieve satisfactory educational outcomes. VR simulation using 360-degree videos and HMDs could serve as an effective alternative form of clinical training in mental health nursing. Education could be enhanced by its benefits of being engaging and exciting, as reported by this study's participants.

To have an objective depression diagnosis, numerous studies based on machine learning and deep learning using electroencephalogram (EEG) have been conducted. Most studies depend on one-dimensional raw data and required fine feature extraction. To solve this problem, in the EEG visualization research field, short-time Fourier transform (STFT), wavelet, and coherence commonly used as method s for transferring EEG data to 2D images. However, we devised a new way from the concept that EEG’s asymmetry was considered one of the major biomarkers of depression. This study proposes a deep-asymmetry methodology that converts the EEG’s asymmetry feature into a matrix image and uses it as input to a convolutional neural network. The asymmetry matrix image in the alpha band achieved 98.85% accuracy and outperformed most of the methods presented in previous studies. This study indicates that the proposed method can be an effective tool for pre-screening major depressive disorder patients.

For solar thermal harvesting, an experimental study was performed on the thermal absorption performance of water-based carbon nanotubes (CNTs), Cu, and Al2O3 nanofluids using a halogen lamp-based thermal radiation system. The effect of nanoparticle concentrations (0.01 wt.%, 0.1 wt.%, and 1 wt.%) on the nanofluid dispersion, stability, and thermal absorption characteristics was investigated, and a comparative analysis was performed for each type of nanofluid. All types of nanofluids increased the absorbance and electrical conductivity with increasing nanoparticle concentration, which contributed to improving the thermal absorption performance of nanofluids. The results showed that the thermal absorption performance was high in the order of carbon-based nanofluids (CNTs), metal-based nanofluids (Cu), and oxide-based nanofluids (Al2O3). In CNTs nanofluids, the thermal absorption performance expressed the time reduction rate, which was 12.8%, 16.3%, and 16.4% at 0.01 wt.%, 0.1 wt.%, and 1 wt.% test cases, respectively. Therefore, the 0.1 wt.%-CNTs nanofluid is more economical and appropriate. However, in Al2O3 nanofluids, the time reduction rate of the 1 wt.% nanofluid was significantly higher than that of the 0.01 wt.% and 0.1 wt.% nanofluids. In Cu nanofluids, unlike CNTs and Al2O3 nanofluids, the time reduction rate constantly increased as the nanoparticle concentration increased.

Observation of medical trainees' care performance by experts can be extremely helpful for ensuring safety and providing quality care. The advanced technology of smart glasses enables health professionals to video stream their operations to remote supporters for collaboration and cooperation. This study monitored the clinical situation by using smart glasses for remote cooperative training via video streaming and clinical decision-making through simulation based on a scenario of emergency nursing care for patients with arrhythmia. The clinical operations of bedside trainees, who is Google Glass Enterprise Edition 2(Glass EE2) wearers, were live streamed via their Google Glasses, which were viewed at a remote site by remote supporters via a desktop computer. Data were obtained from 31 nursing students using eight essay questions regarding their experience as desktop-side remote supporters. Most of the participants reported feeling uneasy about identifying clinical situations (84%), patients' condition (72%), and trainees' performance (69%). The current system demonstrated sufficient performance with a satisfactory level of image quality and auditory communication, while network and connectivity are areas that require further improvement. The reported barriers to identifying situations on the remote desktop were predominantly a narrow field of view and motion blur in videos captured by Glass EE2s, and using the customized mirror mode. The current commercial Glass EE2 can facilitate enriched communication between remotely located supporters and trainees by sharing live videos and audio during clinical operations. Further improvement of hardware and software user interfaces will ensure better applicability of smart glasses and video streaming functions to clinical practice settings.

Background Artificial intelligence (AI) technology can enable more efficient decision-making in healthcare settings. There is a growing interest in improving the speed and accuracy of AI systems in providing responses for given tasks in healthcare settings. Objective This study aimed to assess the reliability of ChatGPT in determining emergency department (ED) triage accuracy using the Korean Triage and Acuity Scale (KTAS). Methods Two hundred and two virtual patient cases were built. The gold standard triage classification for each case was established by an experienced ED physician. Three other human raters (ED paramedics) were involved and rated the virtual cases individually. The virtual cases were also rated by two different versions of the chat generative pre-trained transformer (ChatGPT, 3.5 and 4.0). Inter-rater reliability was examined using Fleiss’ kappa and intra-class correlation coefficient (ICC). Results The kappa values for the agreement between the four human raters and ChatGPTs were .523 (version 4.0) and .320 (version 3.5). Of the five levels, the performance was poor when rating patients at levels 1 and 5, as well as case scenarios with additional text descriptions. There were differences in the accuracy of the different versions of GPTs. The ICC between version 3.5 and the gold standard was .520, and that between version 4.0 and the gold standard was .802. Conclusions A substantial level of inter-rater reliability was revealed when GPTs were used as KTAS raters. The current study showed the potential of using GPT in emergency healthcare settings. Considering the shortage of experienced manpower, this AI method may help improve triaging accuracy.

Background and Objectives: Currently, only patients with osteonecrosis of the femoral head (ONFH), who had bone defects involving 30–33.3% of the remaining femoral head, are indicated in hip resurfacing arthroplasty (HRA). In an experimental cadaver model of ONFH involving up to 50% of the remaining femoral head, the initial stability of the femoral head implant (FHI) at the interface between the implant and the remaining femoral head was measured. Materials and Methods: The ten specimens and the remaining ten served as the experimental group and the control group, respectively. We examined the degree of the displacement of the FHI, the bonding strength between the FHI and the retained bone and that at the interface between the FHI and bone cement. Results: Changes in the degree of displacement at the final phase from the initial phase were calculated as 0.089 ± 0.036 mm in the experimental group and 0.083 ± 0.056 mm in the control group. However, this difference reached no statistical significance (p = 0.7789). Overall, there was an increase in the degree of displacement due to the loading stress, with increased loading cycles in both groups. In cycles of up to 6000 times, there was a steep increase. After cycles of 8000 times, however, there was a gradual increase. Moreover, in cycles of up to 8000 times, there was an increase in the difference in the degree of displacement due to the loading stress between the two groups. After cycles of 8000 times, however, such difference remained almost unchanged. Conclusions: In conclusion, orthopedic surgeons could consider performing the HRA in patients with ONFH where the bone defects involved up to 50% of the remaining femoral head, without involving the femoral head–neck junction in the anterior and superior area of the femoral head. However, more evidence-based studies are warranted to justify our results.

Kawasaki disease (KD), a systemic vasculitis and the leading cause of acquired heart disease in children, stems from an uncontrolled inflammatory response that fails to resolve in up to 20% of IVIG-treated patients. This treatment resistance increases the risk of cardiovascular complications and highlights the need for more targeted therapeutics. We used the cell wall extract (LCWE) murine model of KD vasculitis to investigate the therapeutic potential of itaconate, an anti-inflammatory metabolite, in the pathogenesis of KD. The expression of aconitate decarboxylase 1 ( ), which encodes the mitochondrial enzyme that produces itaconate, was assessed in both samples from KD patients and vascular tissues of LCWE-injected mice. LCWE-injected mice were treated with itaconate, and the severity of LCWE-induced KD vasculitis was evaluated. LCWE injection led to the development of cardiovascular lesions, specifically aortitis, coronary arteritis, and abdominal aorta dilatation. Expression of was upregulated in KD patients during the acute phase of the disease and in cardiovascular lesions of LCWE-injected mice. Treatment with itaconate significantly reduced the development of LCWE-induced cardiovascular lesions. Mechanistically, exogenous itaconate suppressed NLRP3 inflammasome activation in LCWE-induced cardiovascular lesions and decreased IL-1β secretion. Itaconate treatment provides cardiovascular protection in an experimental mouse model of KD vasculitis by decreasing NLRP3 inflammasome activation and reducing vascular inflammation. Itaconate may be a promising therapeutic agent for patients with KD.

For the secondary use of clinical documents, it is necessary to de-identify protected health information (PHI) in documents. However, the difficulty lies in the fact that there are few publicly annotated PHI documents. To solve this problem, in this study, we propose a filtered bidirectional encoder representation from transformers (BERT)-based method that predicts a masked word and validates the word again through a similarity filter to construct augmented sentences. The proposed method effectively performs data augmentation. The results show that the augmentation method based on filtered BERT improved the performance of the model. This suggests that our method can effectively improve the performance of the model in the limited data environment.

Background Monkeypox is endemic to African region and has become of Global concern recently due to its outbreaks in non-endemic countries. Although, the disease was first recorded in 1970, no monkeypox specific drug or vaccine exists as of now. Methods We applied drug repositioning method, testing effectiveness of currently approved drugs against emerging disease, as one of the most affordable approaches for discovering novel treatment measures. Techniques such as virtual ligand-based and structure-based screening were applied to identify potential drug candidates against monkeypox. Results We narrowed down our results to 6 antiviral and 20 anti-tumor drugs that exhibit theoretically higher potency than tecovirimat, the currently approved drug for monkeypox disease. Conclusions Our results indicated that selected drug compounds displayed strong binding affinity for p37 receptor of monkeypox virus and therefore can potentially be used in future studies to confirm their effectiveness against the disease.