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Your search keyword '"Kim, Tae Hoon"' showing total 16 results
Start Over Author "Kim, Tae Hoon" Journal journal of clinical medicine
16 results on '"Kim, Tae Hoon"'

2. In-Advance Prediction of Pressure Ulcers via Deep-Learning-Based Robust Missing Value Imputation on Real-Time Intensive Care Variables

Author

Kim, Minkyu, primary, Kim, Tae-Hoon, additional, Kim, Dowon, additional, Lee, Donghoon, additional, Kim, Dohyun, additional, Heo, Jeongwon, additional, Kang, Seonguk, additional, Ha, Taejun, additional, Kim, Jinju, additional, Moon, Da Hye, additional, Heo, Yeonjeong, additional, Kim, Woo Jin, additional, Lee, Seung-Joon, additional, Kim, Yoon, additional, Park, Sang Won, additional, Han, Seon-Sook, additional, and Choi, Hyun-Soo, additional

Published
2023
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3. In-Advance Prediction of Pressure Ulcers via Deep-Learning-Based Robust Missing Value Imputation on Real-Time Intensive Care Variables.

Author

Kim, Minkyu, Kim, Tae-Hoon, Kim, Dowon, Lee, Donghoon, Kim, Dohyun, Heo, Jeongwon, Kang, Seonguk, Ha, Taejun, Kim, Jinju, Moon, Da Hye, Heo, Yeonjeong, Kim, Woo Jin, Lee, Seung-Joon, Kim, Yoon, Park, Sang Won, Han, Seon-Sook, and Choi, Hyun-Soo

Subjects
*CLINICAL decision support systems, *MISSING data (Statistics), *PRESSURE ulcers, *RECEIVER operating characteristic curves, *RECURRENT neural networks
Abstract

Pressure ulcers (PUs) are a prevalent skin disease affecting patients with impaired mobility and in high-risk groups. These ulcers increase patients' suffering, medical expenses, and burden on medical staff. This study introduces a clinical decision support system and verifies it for predicting real-time PU occurrences within the intensive care unit (ICU) by using MIMIC-IV and in-house ICU data. We develop various machine learning (ML) and deep learning (DL) models for predicting PU occurrences in real time using the MIMIC-IV and validate using the MIMIC-IV and Kangwon National University Hospital (KNUH) dataset. To address the challenge of missing values in time series, we propose a novel recurrent neural network model, GRU-D++. This model outperformed other experimental models by achieving the area under the receiver operating characteristic curve (AUROC) of 0.945 for the on-time prediction and AUROC of 0.912 for 48h in-advance prediction. Furthermore, in the external validation with the KNUH dataset, the fine-tuned GRU-D++ model demonstrated superior performances, achieving an AUROC of 0.898 for on-time prediction and an AUROC of 0.897 for 48h in-advance prediction. The proposed GRU-D++, designed to consider temporal information and missing values, stands out for its predictive accuracy. Our findings suggest that this model can significantly alleviate the workload of medical staff and prevent the worsening of patient conditions by enabling timely interventions for PUs in the ICU. [ABSTRACT FROM AUTHOR]

Published
2024
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8. Comparing the Efficacy of Carvedilol and Flecainide on the Treatment of Idiopathic Premature Ventricular Complexes from Ventricular Outflow Tract: A Multicenter, Randomized, Open-Label Pilot Study

Author

Hwang, Jongmin, primary, Oh, Yong-Seog, additional, Park, Hyoung-Seob, additional, Choi, Jong-Il, additional, Lee, Young Soo, additional, Choi, Eue-Keun, additional, Shin, Dong-Gu, additional, On, Young Keun, additional, Kim, Tae-Hoon, additional, Park, Hyung Wook, additional, Cho, Min Soo, additional, Bae, Myung Hwan, additional, and Han, Seongwook, additional

Published
2023
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10. Exploratory Profiling of Extracellular MicroRNAs in Cerebrospinal Fluid Comparing Leptomeningeal Metastasis with Other Central Nervous System Tumor Statuses

Author

Im, Ji Hye, primary, Kim, Tae Hoon, additional, Lee, Kyue-Yim, additional, Gwak, Ho-Shin, additional, Lin, Weiwei, additional, Park, Jong Bae, additional, Kim, Jong Heon, additional, Yoo, Byong Chul, additional, Park, Seong-Min, additional, Kwon, Ji-Woong, additional, Shin, Sang Hoon, additional, and Yoo, Heon, additional

Published
2021
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16. The Role of Exosomes in Bronchoalveloar Lavage from Patients with Acute Respiratory Distress Syndrome.

Author

Kim, Tae Hoon, Hong, Sang-Bum, Lim, Chae-Mann, Koh, Younsuck, Jang, Eun-young, and Huh, Jin Won

Subjects
*ADULT respiratory distress syndrome, *EXOSOMES, *VASCULAR endothelial growth factors
Abstract

Background: Acute respiratory distress syndrome (ARDS) is a life-threatening condition caused by pulmonary and extrapulmonary insults. Exosomes are considered a major cell-to-cell communicator and immune modulator. However, their role in ARDS remains unclear. In this study, we investigated whether exosomes could be a potential biomarker of ARDS. Methods: We isolated exosomes from bronchoalveolar lavage (BAL) of patients with ARDS. The correlation between the level of exosomes with clinical data, including etiology, oxygenation, and 28-day mortality was analyzed. Enzyme-linked immune sorbent assays and western blotting were carried out to characterize BAL exosomes. Immune modulating response of exosomes was investigated by in vitro examination. Results: From 158 patients, we isolated mean 1568.9 µg/mL BAL exosomes, which presented a negative correlation with the PaO2/FiO2 ratio. The level of exosomes did not correlate with 28-day mortality but was elevated in the infectious etiology of ARDS. The exosomes have cargo proteins associated with apoptosis, necroptosis, and autophagy. An in vitro stimulation study revealed that BAL exosomes could induce the production of proinflammatory cytokines and chemokines, but those from patients with ARDS suppressed the production of vascular endothelial growth factor. Conclusions: In ARDS, exosomes are released in alveolar space, and the level is correlated with the etiology of ARDS. BAL exosomes could play an immune-modulating role by controlling the production of cytokines. [ABSTRACT FROM AUTHOR]

Published
2019
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