Purpose: The purpose of this study was to develop an approach to alleviate the discomfort caused by sandbag compression after a bone marrow examination. This research examined the effects of applying a pressure hemostasis band on bleeding, pain, and discomfort at the bone marrow examination site. Methods: This study was conducted with a nonequivalent control group non-synchronized design. For 74 patients under evaluation who underwent bone marrow examination, sandbag compression was applied to the examination site in the control group (n=37), and a pressure hemostasis band was applied to the intervention group (n=37). In both groups, absolute bed rest was performed for two hours, and bleeding, pain, and discomfort at the examination site were measured. Results: After two hours of the bone marrow examination, there was no difference in bleeding on the gauze between the two groups (F=0.59, p=.444). Bleeding occurred in three patients in the intervention group and six in the control group (χ 2 =1.14, p=.479), with no cases of hematoma detected in either group. One hour post-examination, the control group experienced significantly higher pain (F=5.45, p=.022) and discomfort (F=5.68, p=.020) than the intervention group. However, pain and discomfort levels were similar between groups after two hours. Conclusion Compared to the sandbag compression group, the band application group showed no difference in bleeding and experienced less pain and discomfort at the examination site. This confirms that the pressure hemostasis band is a suitable alternative to sandbag compression in post-examination care.

Synthetic data, generated using advanced artificial intelligence (AI) techniques, replicates the statistical properties of real-world datasets while excluding identifiable information.Although synthetic data does not consist of actual data points, it is derived from original datasets, thereby enabling analyses that yield results comparable to those obtained with real data. Synthetic datasets are evaluated based on their utility—a measure of how effectively they mirror real data for analytical purposes. This paper presents the generation of synthetic datasets through the Healthcare Big Data Showcase Project (2019–2023). The original dataset comprises comprehensive multi-omics data from 400 individuals, including cancer survivors, chronic disease patients, and healthy participants. Synthetic data facilitates efficient access and robust analyses, serving as a practical tool for research and education. It addresses privacy concerns, supports AI research, and provides a foundation for innovative applications across diverse fields, such as public health and precision medicine.

Synthetic data, generated using advanced artificial intelligence (AI) techniques, replicates the statistical properties of real-world datasets while excluding identifiable information.Although synthetic data does not consist of actual data points, it is derived from original datasets, thereby enabling analyses that yield results comparable to those obtained with real data. Synthetic datasets are evaluated based on their utility—a measure of how effectively they mirror real data for analytical purposes. This paper presents the generation of synthetic datasets through the Healthcare Big Data Showcase Project (2019–2023). The original dataset comprises comprehensive multi-omics data from 400 individuals, including cancer survivors, chronic disease patients, and healthy participants. Synthetic data facilitates efficient access and robust analyses, serving as a practical tool for research and education. It addresses privacy concerns, supports AI research, and provides a foundation for innovative applications across diverse fields, such as public health and precision medicine.

Background: Primary cutaneous CD30+ lymphoproliferative disorders (pcCD30-LPDs) are a diseases with various clinical and prognostic characteristics. Objective: Increasing our knowledge of the clinical characteristics of pcCD30-LPDs and identifying potential prognostic variables in an Asian population. Methods: Clinicopathological features and survival data of pcCD30-LPD cases obtained from 22 hospitals in South Korea were examined. Results: A total of 413 cases of pcCD30-LPDs (lymphomatoid papulosis [LYP], n=237; primary cutaneous anaplastic large cell lymphoma [C-ALCL], n=176) were included. Ninety percent of LYP patients and roughly 50% of C-ALCL patients presented with multiple skin lesions. Both LYP and C-ALCL affected the lower limbs most frequently. Multiplicity and advanced T stage of LYP lesions were associated with a chronic course longer than 6 months. Clinical morphology with patch lesions and elevated serum lactate dehydrogenase were significantly associated with LPDs during follow-up in LYP patients. Extracutaneous involvement of C-ALCL occurred in 13.2% of patients. Lesions larger than 5 cm and increased serum lactate dehydrogenase were associated with a poor prognosis in C-ALCL. The survival of patients with C-ALCL was unaffected by the anatomical locations of skin lesions or other pathological factors. Conclusion The multiplicity or size of skin lesions was associated with a chronic course of LYP and survival among patients with C-ALCL.

Purpose: The study aims to confirm the mediating effect of nursing professional pride in the relationship between nursing practice environment, nursing performance, and retention intention. Methods: A descriptive cross-sectional survey was conducted from December 13 to 31, 2021, involving 127 nurses. The following statistical analysis was conducted: t-test, ANOVA, Scheffé test, Pearson's correlation coefficient analysis, and Hayes Process Macro Model 4 (to test the mediating effect). Results: Nursing practice environment showed a significant positive correlation with nursing performance, retention intention, and nursing professional pride. Nursing practice performance showed a positive correlation with retention intention and nursing professional pride, and retention intention showed a significant positive correlation with nursing professional pride. The mediating effect of nursing professional pride was found in the effect of nurses' nursing practice environment on their retention intention. In addition, the mediating effect of nursing professional pride was found in the effect of nurses' nursing practice performance on their retention intention. Conclusion Through this study, it was confirmed that nursing professional pride is a major A factor affecting retention intention in the hospital. Therefore, in order to increase nurses' retention intention to remain in Hospital, the basis of basic data was presented for strategy development.

Purpose: The study aims to confirm the mediating effect of nursing professional pride in the relationship between nursing practice environment, nursing performance, and retention intention. Methods: A descriptive cross-sectional survey was conducted from December 13 to 31, 2021, involving 127 nurses. The following statistical analysis was conducted: t-test, ANOVA, Scheffé test, Pearson's correlation coefficient analysis, and Hayes Process Macro Model 4 (to test the mediating effect). Results: Nursing practice environment showed a significant positive correlation with nursing performance, retention intention, and nursing professional pride. Nursing practice performance showed a positive correlation with retention intention and nursing professional pride, and retention intention showed a significant positive correlation with nursing professional pride. The mediating effect of nursing professional pride was found in the effect of nurses' nursing practice environment on their retention intention. In addition, the mediating effect of nursing professional pride was found in the effect of nurses' nursing practice performance on their retention intention. Conclusion Through this study, it was confirmed that nursing professional pride is a major A factor affecting retention intention in the hospital. Therefore, in order to increase nurses' retention intention to remain in Hospital, the basis of basic data was presented for strategy development.

Purpose: The purpose of this study was to develop an approach to alleviate the discomfort caused by sandbag compression after a bone marrow examination. This research examined the effects of applying a pressure hemostasis band on bleeding, pain, and discomfort at the bone marrow examination site. Methods: This study was conducted with a nonequivalent control group non-synchronized design. For 74 patients under evaluation who underwent bone marrow examination, sandbag compression was applied to the examination site in the control group (n=37), and a pressure hemostasis band was applied to the intervention group (n=37). In both groups, absolute bed rest was performed for two hours, and bleeding, pain, and discomfort at the examination site were measured. Results: After two hours of the bone marrow examination, there was no difference in bleeding on the gauze between the two groups (F=0.59, p=.444). Bleeding occurred in three patients in the intervention group and six in the control group (χ 2 =1.14, p=.479), with no cases of hematoma detected in either group. One hour post-examination, the control group experienced significantly higher pain (F=5.45, p=.022) and discomfort (F=5.68, p=.020) than the intervention group. However, pain and discomfort levels were similar between groups after two hours. Conclusion Compared to the sandbag compression group, the band application group showed no difference in bleeding and experienced less pain and discomfort at the examination site. This confirms that the pressure hemostasis band is a suitable alternative to sandbag compression in post-examination care.

Purpose: The study aims to confirm the mediating effect of nursing professional pride in the relationship between nursing practice environment, nursing performance, and retention intention. Methods: A descriptive cross-sectional survey was conducted from December 13 to 31, 2021, involving 127 nurses. The following statistical analysis was conducted: t-test, ANOVA, Scheffé test, Pearson's correlation coefficient analysis, and Hayes Process Macro Model 4 (to test the mediating effect). Results: Nursing practice environment showed a significant positive correlation with nursing performance, retention intention, and nursing professional pride. Nursing practice performance showed a positive correlation with retention intention and nursing professional pride, and retention intention showed a significant positive correlation with nursing professional pride. The mediating effect of nursing professional pride was found in the effect of nurses' nursing practice environment on their retention intention. In addition, the mediating effect of nursing professional pride was found in the effect of nurses' nursing practice performance on their retention intention. Conclusion Through this study, it was confirmed that nursing professional pride is a major A factor affecting retention intention in the hospital. Therefore, in order to increase nurses' retention intention to remain in Hospital, the basis of basic data was presented for strategy development.

Synthetic data, generated using advanced artificial intelligence (AI) techniques, replicates the statistical properties of real-world datasets while excluding identifiable information.Although synthetic data does not consist of actual data points, it is derived from original datasets, thereby enabling analyses that yield results comparable to those obtained with real data. Synthetic datasets are evaluated based on their utility—a measure of how effectively they mirror real data for analytical purposes. This paper presents the generation of synthetic datasets through the Healthcare Big Data Showcase Project (2019–2023). The original dataset comprises comprehensive multi-omics data from 400 individuals, including cancer survivors, chronic disease patients, and healthy participants. Synthetic data facilitates efficient access and robust analyses, serving as a practical tool for research and education. It addresses privacy concerns, supports AI research, and provides a foundation for innovative applications across diverse fields, such as public health and precision medicine.

Synthetic data, generated using advanced artificial intelligence (AI) techniques, replicates the statistical properties of real-world datasets while excluding identifiable information.Although synthetic data does not consist of actual data points, it is derived from original datasets, thereby enabling analyses that yield results comparable to those obtained with real data. Synthetic datasets are evaluated based on their utility—a measure of how effectively they mirror real data for analytical purposes. This paper presents the generation of synthetic datasets through the Healthcare Big Data Showcase Project (2019–2023). The original dataset comprises comprehensive multi-omics data from 400 individuals, including cancer survivors, chronic disease patients, and healthy participants. Synthetic data facilitates efficient access and robust analyses, serving as a practical tool for research and education. It addresses privacy concerns, supports AI research, and provides a foundation for innovative applications across diverse fields, such as public health and precision medicine.