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.

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.

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/Aims: Little attention is paid to chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) in Korea due to the rarity of the disease. With its rising incidence, we aimed to evaluate recent changes in treatment patterns and survival outcomes of patients with CLL/SLL. Methods: A total of 141 patients diagnosed with CLL/SLL between January 2010 and March 2020 who received systemic therapy were analyzed in this multicenter retrospective study. Results: The median patient age was 66 years at diagnosis, and 68.1% were male. The median interval from diagnosis to initial treatment was 0.9 months (range: 0–77.6 months), and the most common treatment indication was progressive marrow failure (50.4%). Regarding first-line therapy, 46.8% received fludarabine, cyclophosphamide, plus rituximab (FCR), followed by chlorambucil (19.9%), and obinutuzumab plus chlorambucil (GC) (12.1%). The median progression-free survival (PFS) was 49.3 months (95% confidence interval [CI], 32.7–61.4), and median overall survival was not reached (95% CI, 98.4 mo– not reached). Multivariable analysis revealed younger age (≤ 65 yr) (hazard ratio [HR], 0.46; p < 0.001) and first-line therapy with FCR (HR, 0.64; p = 0.019) were independently associated with improved PFS. TP53 aberrations were observed in 7.0% (4/57) of evaluable patients. Following reimbursement, GC became the most common therapy among patients over 65 years and second in the overall population after 2017. Conclusions Age and reimbursement mainly influenced treatment strategies. Greater effort to apply risk stratifications into practice and clinical trials for novel agents could help improve treatment outcomes in Korean patients.

Background: Papillary breast lesions (PBLs) comprise diverse entities from benign and atypical lesions to malignant tumors. Although PBLs are characterized by a papillary growth pattern, it is challenging to achieve high diagnostic accuracy and reproducibility. Thus, we investigated the diagnostic reproducibility of PBLs in core needle biopsy (CNB) specimens with World Health Organization (WHO) classification. Methods: Diagnostic reproducibility was assessed using interobserver variability (kappa value, κ) and agreement rate in the pathologic diagnosis of 60 PBL cases on CNB among 20 breast pathologists affiliated with 20 medical institutions in Korea. This analysis was performed using hematoxylin and eosin (H&E) staining and immunohistochemical (IHC) staining for cytokeratin 5 (CK5) and p63. The pathologic diagnosis of PBLs was based on WHO classification, which was used to establish simple classifications (4-tier, 3-tier, and 2-tier). Results: On WHO classification, H&E staining exhibited ‘fair agreement’ (κ = 0.21) with a 47.0% agreement rate. Simple classifications presented improvement in interobserver variability and agreement rate. IHC staining increased the kappa value and agreement rate in all the classifications. Despite IHC staining, the encapsulated/solid papillary carcinoma (EPC/SPC) subgroup (κ = 0.16) exhibited lower agreement compared to the non-EPC/SPC subgroup (κ = 0.35) with WHO classification, which was similar to the results of any other classification systems. Conclusions Although the use of IHC staining for CK5 and p63 increased the diagnostic agreement of PBLs in CNB specimens, WHO classification exhibited a higher discordance rate compared to any other classifications. Therefore, this result warrants further intensive consensus studies to improve the diagnostic reproducibility of PBLs with WHO classification.

BACKGROUND/OBJECTIVES: This study was designed to investigate the improvement effect of white ginseng extract (GS-KG9) on D-galactosamine (Ga1N)-induced oxidative stress and liver injury. SUBJECTS/METHODS: Sixty Sprague-Dawley rats were divided into 6 groups. Rats were orally administrated with GS-KG9 (300, 500, or 700 mg/kg) or silymarin (25 mg/kg) for 2 weeks. The rats of the GS-KG9- and silymarin-treated groups and a control group were then intraperitoneally injected Ga1N at a concentration of 650 mg/kg for 4 days. To investigate the protective effect of GS-KG9 against GalN-induced liver injury, blood liver function indicators, anti-oxidative stress indicators, and histopathological features were analyzed. RESULTS: Serum biochemical analysis indicated that GS-KG9 ameliorated the elevation of aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), and lactate dehydrogenase (LDH) in GalN-treated rats. The hepatoprotective effects of GS-KG9 involved enhancing components of the hepatic antioxidant defense system, including glutathione, glutathione peroxidase (GPx), superoxide dismutase (SOD), and catalase (CAT). In addition, GS-KG9 treatment inhibited reactive oxygen species (ROS) production induced by GalN treatment in hepatocytes and significantly increased the expression levels of nuclear factor erythroid-2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1) proteins, which are antioxidant proteins. In particular, by histological analyses bases on hematoxylin and eosin, Masson's trichrome, α-smooth muscle actin, and transforming growth factor-β1 staining, we determined that the administration of 500 mg/kg GS-KG9 inhibited hepatic inflammation and fibrosis due to the excessive accumulation of collagen. CONCLUSIONS These findings demonstrate that GS-KG9 improves GalN-induced liver inflammation, necrosis, and fibrosis by attenuating oxidative stress. Therefore, GS-KG9 may be considered a useful candidate in the development of a natural preventive agent against liver injury.

BACKGROUND: Precise measuring and monitoring of physical activity (PA) in patients with cerebral palsy (CP) are critical for assessing their PA participation and its potential health benefits. Accelerometer-based assessment of PA has been considered valid, reliable, and practical in children with CP. Therefore, we investigated the correlation between accelerometer- and questionnaire-based assessment of PA in CP patients. METHODS: Nineteen patients with CP who were classified as Gross Motor Function Classification System level I–III and 84 normally developed participants were included in the study. Study participants wore an accelerometer for seven days, after which they visited the hospital and completed the International Physical Activity Questionnaire (IPAQ). CP patients and their caregivers completed the Pediatric Outcomes Data Collection Instrument (PODCI) and the Caregiver Priorities and Child Health Index of Life with Disabilities, respectively. The concurrent validity of the questionnaires was assessed. RESULTS: In the accelerometer-based assessment, time spent in PA was significantly shorter at every intensity level in CP patients than in normally developed participants. However, PA assessed by the IPAQ was significantly higher in patients with CP, indicating that they tend to exaggerate their participation in PA. On the correlation of the assessment by the accelerometer and by the PODCI, transfer/basic mobility, sports/physical function, and happiness increased significantly as the number of steps taken and the distance travelled increased. CONCLUSIONS In patients with CP, happiness and quality of life are associated with higher levels of PA. Thus, programs for patients with CP should focus on improving their PA.

OBJECTIVE: In terms of efficacy, several previous studies have shown that the success rate in inhibiting preterm labor was not different between magnesium sulfate and ritodrine. However, there is a paucity of information regarding the efficacy of both medications after consideration of intra-amniotic infection, which is one of the most important prognostic factors in patients of threatened preterm birth. The objective of this study was to compare the efficacy and safety of magnesium sulfate with that of ritodrine in preterm labor. METHODS: In this retrospective cohort study, we included patients who were admitted and treated with either ritodrine or magnesium sulfate with the diagnosis of preterm labor at 24–33.6 weeks of gestational age between January 2005 to April 2015. Patients were divided into 2 groups according to the first-used tocolytics (ritodrine group and magnesium sulfate group). We compared the efficacy and prevalence of side effect in each group. The efficacy of both tocolytics was evaluated in terms of preterm delivery within 48 hours, 7 days, or 37 weeks of gestation and need for 2nd line therapy. RESULTS: A total number of 201 patients were enrolled including 177 cases in ritodrine group and 24 cases in magnesium sulfate group. The efficacy of both tocolytics (preterm delivery within 48 hours, 7 days, or 37 weeks of gestation and need for 2nd line therapy) was not different between the 2 groups of cases. In multivariate analysis, gestational age at treatment, twin gestation, intra-amniotic infection and maternal C-reactive protein (CRP) was associated with treatment failure (preterm delivery within 48 hours), but the type of tocolytics was not significantly associated with treatment failure. The type of side effect was different in the 2 groups, but the frequency of total adverse effect, need for discontinuation of therapy because of maternal adverse effect, and severe adverse effect were not different between the two groups of cases. CONCLUSION: The efficacy and safety of magnesium sulfate was similar to ritodrine, and can be a substitute tocolytics. Additionally, failure of tocolytic therapy was determined by gestational age at treatment, twin gestation, intra-amniotic infection, and maternal CRP, not by the type of tocolytics.
C-Reactive Protein ; Cohort Studies ; Diagnosis ; Female ; Gestational Age ; Humans ; Magnesium Sulfate ; Magnesium ; Multivariate Analysis ; Obstetric Labor, Premature ; Pregnancy ; Premature Birth ; Prevalence ; Retrospective Studies ; Ritodrine ; Tocolysis ; Tocolytic Agents ; Treatment Failure ; Twins