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by Byungseok Kang, Youngjae Jo
Recently, Generative Adversarial Networks (GAN) has been greatly developed and widely used in image synthesis. A Style-Based Generator Architecture for Generative Adversarial Networks (StyleGAN) which is the foremost, continues to develop human face inversion domain. StyleGAN uses insufficient vector space to express more than one million pixels. It is difficult to apply in real business due to distortion-edit tradeoff problem in latent space. To overcome this, we propose a novel semantic segment encoder (SSE) with improved face inversion quality by narrowing the size of restoration latent space. Encoder’s learning area is minimized to logical semantic-segment units that can be recognized by humans. The proposed encoder does not affect other segments because only one segment is edited at a time. To verify the face inversion quality, we compared with the latest encoders both Pixel2style2Pixel and RestyleEncoder. Experimental result shows that the proposed encoder improved distortion quality around 20% while maintain editing performance.
Previous systematic reviews and meta-analyses have mainly focused on improvements in the number of metabolic syndrome risk factors and individual changes in each risk factor, making it challenging to examine the impact of comprehensive lifestyle modification interventions on adherence to recommended health behaviors. To address this gap, we conducted a systematic and meta-analysis aimed at identifying clinical parameter levels associated with lifestyle modification outcomes and adherence to recommended health behaviors for individuals with metabolic syndrome.
A total of seven studies retrieved from four databases (CINAHL, Medline via PubMed, American Psychological Association PsycINFO, and Embase) were included in the review. The selected studies, which demonstrated improvements in health behaviors, all included diet and exercise as main factors of comprehensive lifestyle modification in home settings.
Our findings suggest that a 6-month comprehensive intervention including diet and exercise can be effective in decreasing glucose levels and systolic blood pressure. However, given the limited available data, further studies investigating the efficacy of interventions of varying durations are needed.
Although our review included a small number of studies, comprehensive lifestyle modifications consisting of at least two components (primarily diet and exercise) can improve health behaviors and some clinical parameters among individuals with metabolic syndrome. Future studies are needed to investigate the long-term effects of lifestyle modifications on health behavior adherence and explore effective interventions to address certain clinical parameters, such as high-density lipoprotein levels. Also, we recommend using objective and quantifiable measure to compare adherence to recommended lifestyle modifications across studies.
This research provides empirical evidence of the effectiveness of comprehensive lifestyle modification and emphasizes the need to develop long-term nursing strategies in public health that can be used to effectively manage metabolic syndrome.
by Ki-Hoon Kim, Seol Whan Oh, Soo Jeong Ko, Kang Hyuck Lee, Wona Choi, In Young Choi
Numerous studies make extensive use of healthcare data, including human materials and clinical information, and acknowledge its significance. However, limitations in data collection methods can impact the quality of healthcare data obtained from multiple institutions. In order to secure high-quality data related to human materials, research focused on data quality is necessary. This study validated the quality of data collected in 2020 from 16 institutions constituting the Korea Biobank Network using 104 validation rules. The validation rules were developed based on the DQ4HEALTH model and were divided into four dimensions: completeness, validity, accuracy, and uniqueness. Korea Biobank Network collects and manages human materials and clinical information from multiple biobanks, and is in the process of developing a common data model for data integration. The results of the data quality verification revealed an error rate of 0.74%. Furthermore, an analysis of the data from each institution was performed to examine the relationship between the institution’s characteristics and error count. The results from a chi-square test indicated that there was an independent correlation between each institution and its error count. To confirm this correlation between error counts and the characteristics of each institution, a correlation analysis was conducted. The results, shown in a graph, revealed the relationship between factors that had high correlation coefficients and the error count. The findings suggest that the data quality was impacted by biases in the evaluation system, including the institution’s IT environment, infrastructure, and the number of collected samples. These results highlight the need to consider the scalability of research quality when evaluating clinical epidemiological information linked to human materials in future validation studies of data quality.
by Insoo Kim, Junhee Seok, Yoojoong Kim
Traditionally, datasets with multiple censored time-to-events have not been utilized in multivariate analysis because of their high level of complexity. In this paper, we propose the Censored Time Interval Analysis (CTIVA) method to address this issue. It estimates the joint probability distribution of actual event times in the censored dataset by implementing a statistical probability density estimation technique on the dataset. Based on the acquired event time, CTIVA investigates variables correlated with the interval time of events via statistical tests. The proposed method handles both categorical and continuous variables simultaneously—thus, it is suitable for application on real-world censored time-to-event datasets, which include both categorical and continuous variables. CTIVA outperforms traditional censored time-to-event data handling methods by 5% on simulation data. The average area under the curve (AUC) of the proposed method on the simulation dataset exceeds 0.9 under various conditions. Further, CTIVA yields novel results on National Sample Cohort Demo (NSCD) and proteasome inhibitor bortezomib dataset, a real-world censored time-to-event dataset of medical history of beneficiaries provided by the National Health Insurance Sharing Service (NHISS) and National Center for Biotechnology Information (NCBI). We believe that the development of CTIVA is a milestone in the investigation of variables correlated with interval time of events in presence of censoring.
by Jihun Ahn, HyeYon Yu, Seung-Woon Rha, Byoung Geol Choi, Dong Oh Kang, Cheol Ung Choi, Sangho Park, Jon Seo, Kichang Kim, Minung Kim, Yong Hoon Kim, Yong Seong Seo
This prospective, multicenter, randomized study aimed to compare the 1-year clinical outcomes after primary stenting with self-expanding bare metal nitinol stent (SENS) and plain old balloon angioplasty (POBA) in patients with critical limb ischemia (CLI) and below-the-knee (BTK) lesions. Overall, 119 patients with CLI and BTK lesions were randomized to POBA alone (POBA group, 61 patients) or primary stenting with SENS (stenting group, 58 patients) after achieving acceptable POBA results in target BTK lesions. Clinical outcomes including amputation and revascularization rates were prospectively compared for 1 year. After 1 year, similar incidence rates of individual clinical endpoints, including cardiac death (6.5% vs. 5.1%, p > 0.999), myocardial infarction (1.6% vs. 0.0%, p > 0.999), repeat revascularization (19.6% vs. 18.9%, p = 0.922), target lesion revascularization (13.1% vs. 17.2%, p = 0.530), and amputation (4.9% vs. 0.0%, p = 0.244), were observed. POBA appeared to have acceptable treatment outcomes compared with primary stenting with SENS after 1 year in CLI patients with BTK lesions undergoing percutaneous transluminal angioplasty (PTA).
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