MRI-based Deep Learning Algorithm for Assisting Clinically Significant Prostate Cancer Detection: A Bicenter Prospective Study.

Background Although artificial intelligence is actively being developed for prostate MRI, few studies have prospectively validated these tools. Purpose To compare the diagnostic performance of a commercial deep learning algorithm (DLA) and radiologists' clinical reports for cancer detection in participants from two hospitals using histopathologic findings from biopsy specimens as the reference standard. Materials and Methods This prospective bicenter study enrolled participants suspected of having prostate cancer (PCa) who were scheduled for biopsy based on clinical information, including prostate MRI, from December 2022 to July 2023.

Gender differences in occupational hazard exposures within the same occupation: A nationally representative analysis in South Korea.

Objective: Occupational health researchers have often treated gender as a confounder in epidemiologic studies, but gender may influence exposure profiles. This study investigated gender differences in occupational hazard exposures within the same occupation.

Methods: We analyzed the 6 Korean Working Conditions Survey (2020), a nationally representative dataset from South Korea.

A Review of Mendelian Randomization: Assumptions, Methods, and Application to Obesity-Related Diseases.

Mendelian randomization (MR) is a statistical method that uses genetic variants as instrumental variables to estimate the causal effect of exposure on an outcome in the presence of unmeasured confounding. In this review, we argue that it is crucial to acknowledge the instrumental variable assumptions in MR analysis. We describe widely used MR methods, using an example from obesity-related metabolic disorders.

Sensitivity Analysis for Effects of Multiple Exposures in the Presence of Unmeasured Confounding.

Epidemiological research aims to investigate how multiple exposures affect health outcomes of interest, but observational studies often suffer from biases caused by unmeasured confounders. In this study, we develop a novel sensitivity model to investigate the effect of correlated multiple exposures on the continuous health outcomes of interest. The proposed sensitivity analysis is model-agnostic and can be applied to any machine learning algorithm.

Associations between breastfeeding and breast cancer risk through mammographic breast density in a cohort of Korean women.

Background: Mammographic breast density has been suggested to play a role as a mediator between the risk factors for breast cancer (BC) and BC risk. We investigated the extent to which never breastfeeding is a risk factor for BC and how this risk is further mediated by increased mammographic breast density.

Methods: This retrospective cohort study included 4 136 723 women aged ≥40 years who underwent mammographic screening between 2009 and 2010 and were followed up until 31 December 2020.

Sensitivity Analysis for Effects of Multiple Exposures in the Presence of Unmeasured Confounding: Non-Gaussian and Time-to-Event Outcomes.

In epidemiological studies, evaluating the health impacts stemming from multiple exposures is one of the important goals. To analyze the effects of multiple exposures on discrete or time-to-event health outcomes, researchers often employ generalized linear models, Cox proportional hazards models, and machine learning methods. However, observational studies are prone to unmeasured confounding factors, which can introduce the potential for substantial bias in the multiple exposure effects.

Dynamic Performance and Power Optimization with Heterogeneous Processing-in-Memory for AI Applications on Edge Devices.

The rapid advancement of artificial intelligence (AI) technology, combined with the widespread proliferation of Internet of Things (IoT) devices, has significantly expanded the scope of AI applications, from data centers to edge devices. Running AI applications on edge devices requires a careful balance between data processing performance and energy efficiency. This challenge becomes even more critical when the computational load of applications dynamically changes over time, making it difficult to maintain optimal performance and energy efficiency simultaneously.

Sensitivity Analysis for Attributable Fraction in the Presence of Unmeasured Confounding.

A main goal of epidemiology is to provide an impact of an exposure on health outcomes. The attributable fraction (AF) is a widely used measure for quantifying its contribution. Various methods have been developed to estimate AF, including standardization, inverse probability of treatment weighting, and doubly robust methods.

Sensitivity analysis for unmeasured confounding in estimating the difference in restricted mean survival time.

The difference in restricted mean survival time has been increasingly used as an alternative measure to the hazard ratio in survival analysis. Although some statistical methods have been developed for estimating the difference in restricted mean survival time adjusted for measured confounders in observational studies, the impact of unmeasured confounding on the estimate has rarely been assessed. We develop a novel sensitivity analysis for the estimate of the difference in restricted mean survival time with respect to unmeasured confounding.

Genetic determinants of obesity in Korean populations: exploring genome-wide associations and polygenic risk scores.

East Asian populations exhibit a genetic predisposition to obesity, yet comprehensive research on these traits is limited. We conducted a genome-wide association study (GWAS) with 93,673 Korean subjects to uncover novel genetic loci linked to obesity, examining metrics such as body mass index, waist circumference, body fat ratio, and abdominal fat ratio. Participants were categorized into non-obese, metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO) groups.

Regional inequalities in excess mortality and its community determinants during the early COVID-19 pandemic in South Korea.

Background: Excess mortality during the COVID-19 pandemic provides a comprehensive measure of disease burden, and its local variation highlights regional health inequalities. We investigated local excess mortality in 2020 and its determinants at the community level.

Methods: We collected data from 250 districts in South Korea, including monthly all-cause mortality for 2015-2020 and community characteristics from 2019.

The effect of dialysis modality on annual mortality: A prospective cohort study.

Despite numerous studies on the effect of each dialysis modality on mortality, the issue remains controversial. We investigated the hazard rate of mortality in patients with incident end-stage renal disease (ESRD) concerning initial dialysis modality (hemodialysis vs. peritoneal dialysis).

Preservation of Topological Surface States in Millimeter-Scale Transferred Membranes.

Ultrathin topological insulator membranes are building blocks of exotic quantum matter. However, traditional epitaxy of these materials does not facilitate stacking in arbitrary orders, while mechanical exfoliation from bulk crystals is also challenging due to the non-negligible interlayer coupling therein. Here we liberate millimeter-scale films of the topological insulator BiSe, grown by molecular beam epitaxy, down to 3 quintuple layers.

Diabetic Neuropathy and Minimum Effective Anesthetic Concentration of Mepivacaine for Axillary Brachial Plexus Block: A Prospective Observational Study.

Nerves in patients with diabetic neuropathy (DN) show increased susceptibility to local anesthetics, potentially requiring a decreased dose. We investigated whether the minimum effective anesthetic concentration (MEAC) of mepivacaine for successful axillary block is lower in patients with DN than in those without. This prospective observational study included patients with DN ( = 22) and without diabetes ( = 22) at a tertiary care center.

Outcomes of Various Classes of Oral Antidiabetic Drugs on Nonalcoholic Fatty Liver Disease.

Importance: Several oral antidiabetic drug (OAD) classes can potentially improve patient outcomes in nonalcoholic fatty liver disease (NAFLD) to varying degrees, but clinical data on which class is favored are lacking.

Objective: To investigate which OAD is associated with the best patient outcomes in NAFLD and type 2 diabetes (T2D).

Design, Setting, And Participants: This retrospective nonrandomized interventional cohort study used the National Health Information Database, which provided population-level data for Korea.

Prediction of low-density lipoprotein cholesterol levels using machine learning methods.

Objective: Low-density lipoprotein cholesterol (LDL-C) has been commonly calculated by equations, but their performance has not been entirely satisfactory. This study aimed to develop a more accurate LDL-C prediction model using machine learning methods.

Methods: The study involved predicting directly measured LDL-C, using individual characteristics, lipid profiles, and other laboratory results as predictors.

Association with Combined Occupational Hazards Exposure and Risk of Metabolic Syndrome: A Workers' Health Examination Cohort 2012-2021.

Background: This study aimed to evaluate the association between exposure to occupational hazards and the metabolic syndrome. A secondary objective was to analyze the additive and multiplicative effects of exposure to risk factors.

Methods: This retrospective cohort was based on 31,615 health examinees at the Pusan National University Yangsan Hospital in Republic of Korea from 2012-2021.

Characteristics of fatal occupational injuries in migrant workers in South Korea: A machine learning study.

Objective: Analysis of occupational injuries is essential for developing preventive strategies. However, few studies have evaluated severe occupational injuries in migrant workers from the perspective of gender. Therefore, using a new analytical method, this study was performed to identify gender-specific characteristics associated with fatal occupational injuries among migrant workers; the interactions between these factors, were also analyzed.