Sangbeom Choi

The development of oral squamous cell carcinoma (OSCC) is a multistep process requiring the accumulation of multiple genetic alterations, influenced by a patient's genetic predisposition as well as by environmental influences, including tobacco, alcohol, chronic inflammation, and viral infection. Tumorigenic genetic alterations consist of two major types: tumor suppressor genes, which promote tumor development when inactivated; and oncogenes, which promote tumor development when activated. Tumor

This RA GSMA confirmed the evidence for HLA loci as the greatest susceptibility factor to RA and showed evidence for linkage at non-HLA loci, such as chromosomes 1p, 6, 8p, 12, 16 and 18q, across studies. These data may provide a basis to carry out targeted linkage and candidate gene studies, particularly in the regions.

Currently, 3D pose estimation methods are not compatible with a variety of low computational power devices because of efficiency and accuracy. In this paper, we revisit a pose estimation architecture from a viewpoint of both efficiency and accuracy. We propose a mobile-friendly model, MobileHumanPose, for real-time 3D human pose estimation from a single RGB image. This model consists of the modified MobileNetV2 backbone, a parametric activation function, and the skip concatenation inspired by U-

BACKGROUND: Increasing evidence suggests that sleep duration is associated with risks of various diseases including type 2 diabetes, cardiovascular disease (CVD), and certain types of cancer. However, the relationship with mortality is not clear, particularly in non-European populations. In this study, we investigated the association between sleep duration and mortality in a population-based prospective cohort of Korean adults. METHODS: This analysis included 34,264 participants (14,704 men and

The aim of this study was to perform a meta-analysis of eligible studies and to derive a precise estimate of the association between interleukin 10 (IL10) polymorphisms and susceptibility to autoimmune thyroid disease (AITD). Meta-analyses were conducted on the associations between AITD and the -1082 G/A (rs1800896), -819 C/T (rs1800871) and -592 C/A (rs1800872) polymorphisms in IL10, and the haplotype of these polymorphisms and AITD. A total of 2903 AITD patients and 3060 controls in 10 eligibl

In the analysis of competing risks data, the cumulative incidence function is a useful quantity to characterize the crude risk of failure from a specific event type. In this article, we consider an efficient semiparametric analysis of mixture component models on cumulative incidence functions. Under the proposed mixture model, latency survival regressions given the event type are performed through a class of semiparametric models that encompasses the proportional hazards model and the proportion

Modern medical treatments have substantially improved survival rates for many chronic diseases and have generated considerable interest in developing cure fraction models for survival data with a non-ignorable cured proportion. Statistical analysis of such data may be further complicated by competing risks that involve multiple types of endpoints. Regression analysis of competing risks is typically undertaken via a proportional hazards model adapted on cause-specific hazard or subdistribution ha

Abstract Censored quantile regression models, which offer great flexibility in assessing covariate effects on event times, have attracted considerable research interest. In this study, we consider flexible estimation and inference procedures for competing risks quantile regression, which not only provides meaningful interpretations by using cumulative incidence quantiles but also extends the conventional accelerated failure time model by relaxing some of the stringent model assumptions, such as

We propose the logistic-kernel smoothing procedure for the semiparametric accelerated failure time (AFT) model with high-dimensional right-censored data. The resulting estimating procedure permits fast and accurate computation of regression parameter estimates and standard errors while preserving the same asymptotic properties as those from the non-smoothed rank estimating function. In addition, we provide an efficient numerical algorithm for obtaining a complete regularization path to facilitat

Abstract This work focuses on a semiparametric analysis of a cure rate modelling approach based on a latent failure process. In clinical and epidemiological studies, a Wiener process with drift may represent a patient's health status and a clinical endpoint occurs when the process first reaches an adverse threshold state. The first‐hitting‐time then follows an inverse‐Gaussian distribution. On the basis of the improper inverse‐Gaussian distribution, we consider a process‐based lifetime model tha

Abstract Cancer patients may die from causes other than the diagnosed cancer. In a study of patients treated for soft tissue sarcoma, the patients may die from the disease or die without experiencing disease recurrence. In addition, a substantial proportion of the patients will remain cancer‐free after surgical resection of the tumour, and therefore will not be at increased risk of any type of failure. Our goal is to describe the effect of adjuvant chemotherapy simultaneously on the probabilitie

We propose a semiparametrically efficient estimation of a broad class of transformation regression models for nonproportional hazards data. Classical transformation models are to be viewed from a frailty model paradigm, and the proposed method provides a unified approach that is valid for both continuous and discrete frailty models. The proposed models are shown to be flexible enough to model long-term follow-up survival data when the treatment effect diminishes over time, a case for which the P