Publications by authors named "Jung Bin Kim"

Article Synopsis
  • * Researchers developed a deep learning model using a ResNet architecture to predict HKA angles from lower limb radiographs, eliminating the need for manual annotations of anatomical landmarks.
  • * The model’s performance was validated using a cohort of 300 knee OA patients, assessing both its accuracy in predicting HKA angles and its effectiveness in classifying the severity of varus deformity, with additional testing on a separate group of 50 patients.
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  • The study investigates how repetitive transcranial magnetic stimulation (rTMS) affects brain structure and clinical outcomes in patients with drug-resistant epilepsy (DRE).
  • Nineteen patients participated, receiving rTMS for 5 days, and changes in gray matter volume were analyzed two months later.
  • Results showed reduced seizure frequency and improved quality of life, linked to increased volume in the cerebellar vermis, suggesting rTMS alters specific brain circuits related to seizure control.
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Cerebral hyperperfusion syndrome (CHS) is a serious complication after bypass surgery in Moyamoya disease (MMD), with autoregulatory dysfunction being a major pathogenesis. This study investigated the change of perioperative autoregulation and preoperative prognostic potentials in MMD with postoperative CHS. Among 26 hemispheres in 24 patients with adult MMD undergoing combined bypass, 13 hemispheres experienced postoperative CHS.

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  • The study highlights the importance of accurately diagnosing acute loss of consciousness (LOC) as different causes require distinct treatments, despite having similar symptoms.
  • Researchers developed AI models that analyze brain connectivity patterns in electroencephalography (EEG) data to differentiate between conditions like nonconvulsive status epilepticus and benzodiazepine intoxication.
  • The convolutional neural network (CNN) model achieved high accuracy in classifying LOC causes, particularly using 20-second EEG data, indicating that these AI tools could significantly improve diagnostic procedures and treatment decisions in clinical settings.
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Neurological disorders such as Parkinson's disease (PD) often adversely affect the vascular system, leading to alterations in blood flow patterns. Functional near-infrared spectroscopy (fNIRS) is used to monitor hemodynamic changes via signal measurement. This study investigated the potential of using resting-state fNIRS data through a convolutional neural network (CNN) to evaluate PD with orthostatic hypotension.

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Determining the laterality of the seizure onset zone is challenging in frontal lobe epilepsy (FLE) due to the rapid propagation of epileptic discharges to the contralateral hemisphere. There is hemispheric lateralization of autonomic control, and heart rate is modulated by interactions between the sympathetic and parasympathetic nervous systems. Based on this notion, the laterality of seizure foci in FLE might be determined using heart rate variability (HRV) parameters.

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Alzheimer's disease (AD) is a progressive disease leading to cognitive decline, and to prevent it, researchers seek to diagnose mild cognitive impairment (MCI) early. Particularly, non-amnestic MCI (naMCI) is often mistaken for normal aging as the representative symptom of AD, memory decline, is absent. Subjective cognitive decline (SCD), an intermediate step between normal aging and MCI, is crucial for prediction or early detection of MCI, which determines the presence of AD spectrum pathology.

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Thermal fatigue cracks occurring in pipes in nuclear power plants pose a high degree of risk. Thermal fatigue cracks are generated when the thermal fatigue load caused by local temperature gradients is repeatedly applied. The flaws are mainly found in welds, owing to the effects of stress concentration caused by the material properties and geometric shapes of welds.

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Motor imagery (MI)-based brain-computer interfaces are widely employed for improving the rehabilitation of paralyzed people and their quality of life. It has been well documented that brain activity patterns in the primary motor cortex and sensorimotor cortex during MI are similar to those of motor execution/imagery. However, individuals paralyzed owing to various neurological disorders have debilitated activation of the motor control region.

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We aimed to compare network properties between focal-onset nonconvulsive status epilepticus (NCSE) and toxic/metabolic encephalopathy (TME) during periods of periodic discharge using graph theoretical analysis, and to evaluate the applicability of graph measures as markers for the differential diagnosis between focal-onset NCSE and TME, using machine learning algorithms. Electroencephalography (EEG) data from 50 focal-onset NCSE and 44 TMEs were analyzed. Epochs with nonictal periodic discharges were selected, and the coherence in each frequency band was analyzed.

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We aimed to identify structural and functional changes in healthy adults with catch-up sleep (CUS), we applied seed-based functional connectivity (FC) analysis using resting-state functional magnetic resonance imaging (MRI). We hypothesized that deficits in reward processing could be a fundamental mechanism underlying the motivation of taking CUS. Then, 55 healthy adults voluntarily (34 with CUS and 21 without CUS) participated in this study.

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  • - The study investigated neural activities and network properties in patients with antihistamine-induced seizures (AIS) compared to seizure-free individuals, hypothesizing that AIS patients have heightened neural synchronization and activity.
  • - Analysis of EEG data revealed that the AIS group exhibited greater spectral power in various brain wave bands and enhanced functional connectivity compared to the seizure-free group, indicating potential neurological differences.
  • - Machine learning models successfully distinguished AIS patients from the seizure-free group with over 99% accuracy, suggesting that the identified neural and network characteristics can aid in diagnosing new-onset seizures clinically.
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Purpose: To delineate the association between otolith function and changes in mean orthostatic blood pressure (BP) and heart rate (HR) in patients with postural orthostatic tachycardia syndrome (POTS).

Methods: Forty-nine patients with POTS were prospectively recruited. We analyzed the results of ocular vestibular-evoked myogenic potentials (oVEMPs) and cervical vestibular-evoked myogenic potentials (cVEMPs), as well as head-up tilt table tests using a Finometer.

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The purpose of this study was to explore different patterns of functional networks between amnestic mild cognitive impairment (aMCI) and non-aMCI (naMCI) using electroencephalography (EEG) graph theoretical analysis. The data of 197 drug-naïve individuals who complained cognitive impairment were reviewed. Resting-state EEG data was acquired.

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Sleep disorder has been portrayed as merely a common dissatisfaction with sleep quality and quantity. However, sleep disorder is actually a medical condition characterized by inconsistent sleep patterns that interfere with emotional dynamics, cognitive functioning, and even physical performance. This is consistent with sleep abnormalities being more common in patients with autonomic dysfunction than in the general population.

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We describe acute vestibular syndrome in a 48-year-old woman with breast cancer who was finally found to have anti-Ma2-associated encephalitis. Although the initial diagnosis was vestibular neuritis elsewhere, progression of symptoms and additional findings of bilateral ptosis and circumlimbal injections, vertical saccadic slowing, and impaired convergence led to a suspicion of a rostral midbrain lesion and final diagnosis. The patient's symptoms and ocular motor signs improved markedly after administration of IV methylprednisolone and oral tacrolimus.

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The inter- and intrarater variability of conventional computed tomography (CT) classification systems for evaluating the extent of ischemic-edematous insult following traumatic brain injury (TBI) may hinder the robustness of TBI prognostic models. This study aimed to employ fully automated quantitative densitometric CT parameters and a cutting-edge machine learning algorithm to construct a robust prognostic model for pediatric TBI. Fifty-eight pediatric patients with TBI who underwent brain CT were retrospectively analyzed.

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Article Synopsis
  • The study looked at how seizures affect social anxiety in people with epilepsy, comparing men and women.
  • Out of 285 people, some had signs of social anxiety, but there was no difference between men and women.
  • The results showed that intractable seizures worsened social anxiety in men, while women felt more anxious in social situations if they didn’t have freedom from seizures in the last year.
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. Limited data are available regarding brain networks in patients with chronic obstructive pulmonary disease (COPD). Here, we investigated brain networks in COPD using graph theoretical analysis of electroencephalography data.

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The purpose of this study was to identify the mechanisms underlying effects of coffee on cognition in the context of brain networks. Here we investigated functional connectivity before and after drinking coffee using graph-theoretic analysis of electroencephalography (EEG). Twenty-one healthy adults voluntarily participated in this study.

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Neurodegenerative change in the central nervous system has been suggested as one of the pathophysiological mechanisms of autonomic nervous system dysfunction in Parkinson's disease (PD). We analyzed gray matter (GM) volume changes and clinical parameters in patients with PD to investigate any involvement in the brain structures responsible for autonomic control in patients with PD having orthostatic hypotension (OH). Voxel-based morphometry was applied to compare regional GM volumes between PD patients with and without OH.

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