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Articles by Kun Ho
Structured multifrequency segmental bioimpedance descriptors for diabetes screening support
ORIGINAL RESEARCH article Volume 17 - 2026 | doi: 10.3389/fphys.2026.1958735 Reviewed by ORIGINAL RESEARCH article MC Minho Choi 1 KH Kun Ho Lee 2 JU Jaeuk U. Kim 1 1. Korea Institute of Oriental Medicine (KIOM), Daejeon, Republic of Korea 2. Chosun University, Dong-gu, Republic of Korea Article metrics View details Abstract Background: Blood-based measurements remain the standard for identifying diabetes mellitus (DM), but repeatable non-invasive approaches may have value for screening support.
Low-Density Lipoprotein Cholesterol Modulates Amyloid-Related Entorhinal Vulnerability and Episodic Memory Performance in Older Adults
ORIGINAL RESEARCH article Front. Aging Neurosci. Sec. Alzheimer's Disease and Related Dementias Abstract Introduction: Cerebral amyloid-beta (Aβ) burden does not fully explain variation in Alzheimer’s disease (AD)-related brain structure and episodic memory. We examined whether circulating low-density lipoprotein cholesterol (LDL-C) modifies the cross-sectional statistical association between Aβ burden, the entorhinal cortex (EC) thickness and episodic memory performance.
Aperiodic EEG signatures: unveiling the interplay between APOE ε4 and mild cognitive impairment subtypes
ORIGINAL RESEARCH article Volume 17 - 2025 | https://doi.org/10.3389/fnagi.2025.1675330 1 Introduction Mild cognitive impairment (MCI), estimated to affect 15%–20% of persons aged 60 and above, is a syndrome characterized by cognitive decline that exceeds a typical person’s age and education level but doesn’t disrupt their activities of daily living (Petersen, 2016).
On robust inference in time series regression
Least squares regression with heteroskedasticity consistent standard errors (“OLS-HC regression”) has proved very useful in cross section environments. However, several major difficulties, which are generally overlooked, must be confronted when transferring the HC technology to time series environments via heteroskedasticity and autocorrelation consistent standard errors (“OLS-HAC regression”).
Prefrontal intra-individual ERP variability and its asymmetry: exploring its biomarker potential in mild cognitive impairment - Alzheimer's Research & Therapy
This study comprised 1,616 participants enlisted from October 2018 to December 2021 at the Gwangju Alzheimer’s Disease and Related Dementias (GARD) center in Gwangju City, South Korea.
Corrigendum: Prefrontal event-related potential markers in association with mild cognitive impairment
In the published article, there was an error. The results of the ERP timings' differences between patients with MCI and healthy individuals were misreported, as “lower” or “reduced” instead of “higher” or “increased/slowed.” A correction has been made to Results, ERP measures, paragraph 1.
Prefrontal event-related potential markers in association with mild cognitive impairment
Joel Eyamu1,2 Wuon-Shik Kim1 Kahye Kim1 Kun Ho Lee3,4,5 Jaeuk U.
Automating Rey Complex Figure Test scoring using a deep learning-based approach: a potential large-scale screening tool for cognitive decline
Alzheimer's Research & Therapy, Aug 2023 The Rey Complex Figure Test (RCFT) has been widely used to evaluate the neurocognitive functions in various clinical groups with a broad range of ages. However, despite its usefulness, the scoring method is as complex as the figure. Such a complicated scoring system can lead to the risk of reducing the extent of agreement among raters.
Machine learning-based quantification for disease uncertainty increases the statistical power of genetic association studies
Allowance for increasingly large samples is a key to identify the association of genetic variants with Alzheimer’s disease (AD) in genome-wide association studies (GWAS). Accordingly, we aimed to develop a method that incorporates patients with mild cognitive impairment (MCI) and unknown cognitive status in GWAS using a machine learning-based AD prediction model.
Automating Rey Complex Figure Test scoring using a deep learning-based approach: a potential large-scale screening tool for cognitive decline - Alzheimer's Research & Therapy
We included participants enrolled in the Gwangju Alzheimer’s and Related Dementia (GARD) cohort registry at Chosun University in Gwangju, Korea, from January 2015 to June 2021. The overall procedure of the GARD database has been previously described [9]. We selected as many images as possible that had been scored by experienced psychologists.
Eye movement changes as an indicator of mild cognitive impairment
1. Introduction Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by the accumulation of amyloid beta (Aβ) plaques and neurofibrillary tau-based tangles, beginning decades before symptoms appear and lead to cognitive decline, with individuals progressing from normal cognitive abilities to prodromal AD and ultimately AD dementia (Jack et al., 2018).
Eye Movement Changes as an Indicator of Mild Cognitive Impairment
Julius Opwonya1, 2, Boncho Ku1, Kun Ho Lee3, 4, Joong Il Kim1* and Jaeuk U. Kim1, 2* 1Korea Institute of Oriental Medicine (KIOM), Republic of Korea 2Korea University of Science and Technology, Republic of Korea 3Chosun University, Republic of Korea 4Korea Brain Research Institute, Republic of Korea The final, formatted version of the article will be published soon.
Prefrontal EEG slowing, synchronization, and ERP peak latency in association with predementia stages of Alzheimer’s disease
Jungmi Choi1, Boncho Ku2, Dieu Ni T. Doan2, 3, Junwoo Park4, Wonseok Cha1, Jaeuk U.
[1710.01691] Context Embedding Networks
Abstract: Low dimensional embeddings that capture the main variations of interest in collections of data are important for many applications. One way to construct these embeddings is to acquire estimates of similarity from the crowd. However, similarity is a multi-dimensional concept that varies from individual to individual.
Efficacy and Safety of Evogliptin Monotherapy in Patients with Type 2 Diabetes and Moderately Elevated HbA1c by Diet and Exercise
To evaluate the efficacy and safety of evogliptin, a newly developed dipeptidyl peptidase-4 inhibitor, in patients with type 2 diabetes (T2D) inadequately controlled by diet and exercise. In this randomized, double-blind, placebo-controlled, parallel-group, multicenter, phase III study, 160 patients with T2D were assigned to either an evogliptin 5?mg or placebo group for 24 weeks. The primary endpoint was the mean change in glycated hemoglobin (HbA1c) from baseline to week 24.
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