Seokjae Heo

We aimed to use deep learning to detect tuberculosis in chest radiographs in annual workers’ health examination data and compare the performances of convolutional neural networks (CNNs) based on images only (I-CNN) and CNNs including demographic variables (D-CNN). The I-CNN and D-CNN models were trained on 1000 chest X-ray images, both positive and negative, for tuberculosis. Feature extraction was conducted using VGG19, InceptionV3, ResNet50, DenseNet121, and InceptionResNetV2. Age, weight, hei

There are several different proposed data mining methods for the postmarketing surveillance of drug safety. Adverse events are often classified into a hierarchical structure. Our objective was to compare the performance of several of these different data mining methods for adverse drug events data with a hierarchical structure. We generated datasets based on the World Health Organization's Adverse Reaction Terminology (WHO-ART) hierarchical structure. We evaluated different data mining methods f

Among biological agents for the treatment of atopic dermatitis (AD), dupilumab is a front-runner. Although many studies have been conducted on the real-world use of dupilumab, the sample size is often small and data is primarily on Western people. Therefore, we investigated the efficacy and safety of dupilumab in patients with moderate-to-severe AD in Korea. All patients with moderate-to-severe AD treated with dupilumab from September 2018 to June 2019 in this institution were included and analy

CRD42021258498.

BACKGROUND: Although disclosing the predictors of different behavioral and psychological symptoms of dementia (BPSD) is the first step in developing person-centered interventions, current understanding is limited, as it considers BPSD as a homogenous construct. This fails to account for their heterogeneity and hinders development of interventions that address the underlying causes of the target BPSD subsyndromes. Moreover, understanding the influence of proximal factors-circadian rhythm-related

Background Triglyceride and glucose (TyG) index and TyG-related indices combined with obesity-related markers are considered important markers of insulin resistance. We aimed to examine the association between the TyG index and modified TyG indices with new-onset hypertension and their predictive ability stratified by sex. Methods and Results We analyzed data from 5414 Korean Genome and Epidemiology Study participants aged 40 to 69 years. Multiple Cox proportional hazard regression analyses were

Dialysis adequacy is an important survival indicator in patients with chronic hemodialysis. However, there are inconveniences and disadvantages to measuring dialysis adequacy by blood samples. This study used machine learning models to predict dialysis adequacy in chronic hemodialysis patients using repeatedly measured data during hemodialysis. This study included 1333 hemodialysis sessions corresponding to the monthly examination dates of 61 patients. Patient demographics and clinical parameter

Previously, we have reported short term effectiveness and safety of dupilumab in Korea. In this study, we are trying to report the long-term effectiveness and safety of dupilumab in Korea. Ninety-nine patients with moderate to severe AD were analyzed. They were evaluated using Eczema Area and Severity Index (EASI), Numerical Rating Scale (NRS), Patient Oriented Eczema Measure (POEM), and Dermatology Quality of Life Index (DLQI) at baseline, week 16, 32 and 52. Efficacy outcomes showed higher imp

The behavioral and psychological symptoms of dementia (BPSD) are challenging aspects of dementia care. This study used machine learning models to predict the occurrence of BPSD among community-dwelling older adults with dementia. We included 187 older adults with dementia for model training and 35 older adults with dementia for external validation. Demographic and health data and premorbid personality traits were examined at the baseline, and actigraphy was utilized to monitor sleep and activity

Bayesian signal detection methods, including the multiitem gamma Poisson shrinker (MGPS), assume a Poisson distribution for the number of reports. However, the database of the adverse event reporting system often has a large number of zero-count cells. A zero-inflated Poisson (ZIP) distribution can be more appropriate in this situation than a Poisson distribution. Few studies have considered ZIP-based models for Bayesian signal detection. In addition, most studies on Bayesian signal detection me

BACKGROUND: Chronic kidney disease (CKD) has emerged as a mounting public health issue worldwide; therefore, prompt identification and prevention are imperative in mitigating CKD-associated complications and mortality rate. We aimed to compare the predictive powers of the homeostatic model assessment for insulin resistance (HOMA-IR) and the metabolic score for insulin resistance (METS-IR) for CKD incidence in middle-aged and older adults. METHODS: This study used longitudinal prospective cohort