• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2012.07a
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• pp.114-118
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• 2012

• The Korean Journal of Physiology and Pharmacology
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• v.23 no.1
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• pp.63-70
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• 2019

We aimed to propose a novel computational approach to predict the electromechanical performance of pre- and post-mitral valve cerclage annuloplasty (MVCA). Furthermore, we tested a virtual estimation method to optimize the left ventricular basement tightening scheme using a pre-MVCA computer model. The present model combines the three-dimensional (3D) electromechanics of the ventricles with the vascular hemodynamics implemented in a lumped parameter model. 3D models of pre- and post-MVCA were reconstructed from the computed tomography (CT) images of two patients and simulated by solving the electromechanical-governing equations with the finite element method. Computed results indicate that reduction of the dilated heart chambers volume (reverse remodeling) appears to be dependent on ventricular stress distribution. Reduced ventricular stresses in the basement after MVCA treatment were observed in the patients who showed reverse remodeling of heart during follow up over 6 months. In the case who failed to show reverse remodeling after MVCA, more virtual tightening of the ventricular basement diameter than the actual model can induce stress unloading, aiding in heart recovery. The simulation result that virtual tightening of the ventricular basement resulted in a marked increase of myocardial stress unloading provides in silico evidence for a functional impact of MVCA treatment on cardiac mechanics and post-operative heart recovery. This technique contributes to establishing a pre-operative virtual rehearsal procedure before MVCA treatment by using patient-specific cardiac electromechanical modeling of pre-MVCA.

• Biomedical Science Letters
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• v.18 no.3
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• pp.210-217
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• 2012

Oncolytic viral vectors have shown good candidates for cancer treatment but have many limitations. To improve the therapeutic potential of oncolytic vaccinia virus, we developed a recombinant vaccinia virus expressing the 4-1BBL co-stimulatory molecule or CCL21. 4-1BBL and CCL21 expression was identified by FACS analysis and immunoblotting. rV-4-1BBL vaccination shows significant tumor regression compared to rV-LacZ, but rV-CCL21 shows rapid tumor growth compared to rV-LacZ in the poorly immunogenic B16 murine melanoma model. 4-1BBL expression resulted in the increase of the number of CD8+ T cells and especially the increase of effector (CD62L-CD44+) CD8+ T cells. These data suggest 4-1BBL may be the potential target for enhancement of tumor immunotherapy.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.2155-2156
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• 2006

The purpose of this work is to investigate the fundamental properties of the gradual muscle force potentiation for the prediction of muscle force and body movement from the stimulation input with musculo-skeletal model. We investigated the dependence of force potentiation on both the pulse-amplitude and the pulse-duration. The experimental result showed that the force increment ratio during electrical stimulation decreased with pulse-amplitude. The force increment ratio decreased with short pulse-duration and was maintained to be constant with pulse-duration longer than $500{\mu}s$. A new model of the muscle potentiation based on these results is desired in the future.

• 한국약용작물학회:학술대회논문집
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• 2008.11a
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• pp.417-418
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• 2008

• Biomedical Science Letters
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• v.28 no.2
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• pp.101-108
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• 2022

High-fat diet (HFD)-fed ovariectomized (OVX) female mice were used as an animal model of obese postmenopausal women. We investigated the effects of ascorbic acid on the histological changes induced in the liver. Plasma alanine aminotransferase levels and liver weights were higher in mice fed an HFD for 18 weeks than in mice fed a low-fat diet, effects that were inhibited by ascorbic acid. Similarly, mice fed an ascorbic acid-supplemented HFD had less hepatic lipid accumulation than did mice fed an HFD alone. Moreover, administration of ascorbic acid reduced inflammatory cells, including mast cells and CD68-positive cells, and inflammatory foci in the liver and inhibited hepatocyte ballooning. Hepatic collagen levels were lower in ascorbic acid-treated versus non-treated mice. These results suggest that ascorbic acid inhibits hepatic steatosis, inflammation, and fibrosis in obese OVX mice. Thus, ascorbic acid intake may be useful for postmenopausal women with nonalcoholic fatty liver disease.

• Journal of Biomedical Engineering Research
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• v.41 no.2
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• pp.94-100
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• 2020

The purpose of this study was to present the models for classifying the wrist X-ray images by types and for segmenting the radius automatically in each image using deep learning and to verify the learned models. The data were a total of 904 wrist X-rays with the distal radius fracture, consisting of 472 anteroposterior (AP) and 432 lateral images. The learning model was the ResNet50 model for AP/lateral image classification, and the U-Net model for segmentation of the radius. In the model for AP/lateral image classification, 100.0% was showed in precision, recall, and F1 score and area under curve (AUC) was 1.0. The model for segmentation of the radius showed an accuracy of 99.46%, a sensitivity of 89.68%, a specificity of 99.72%, and a Dice similarity coefficient of 90.05% in AP images and an accuracy of 99.37%, a sensitivity of 88.65%, a specificity of 99.69%, and a Dice similarity coefficient of 86.05% in lateral images. The model for AP/lateral classification and the segmentation model of the radius learned through deep learning showed favorable performances to expect clinical application.

• Journal of Computing Science and Engineering
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• v.2 no.2
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• pp.109-136
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• 2008

In this survey paper, we discuss biomedical ontologies and major text mining techniques applied to biomedicine and healthcare. Biomedical ontologies such as UMLS are currently being adopted in text mining approaches because they provide domain knowledge for text mining approaches. In addition, biomedical ontologies enable us to resolve many linguistic problems when text mining approaches handle biomedical literature. As the first example of text mining, document clustering is surveyed. Because a document set is normally multiple topic, text mining approaches use document clustering as a preprocessing step to group similar documents. Additionally, document clustering is able to inform the biomedical literature searches required for the practice of evidence-based medicine. We introduce Swanson's UnDiscovered Public Knowledge (UDPK) model to generate biomedical hypotheses from biomedical literature such as MEDLINE by discovering novel connections among logically-related biomedical concepts. Another important area of text mining is document classification. Document classification is a valuable tool for biomedical tasks that involve large amounts of text. We survey well-known classification techniques in biomedicine. As the last example of text mining in biomedicine and healthcare, we survey information extraction. Information extraction is the process of scanning text for information relevant to some interest, including extracting entities, relations, and events. We also address techniques and issues of evaluating text mining applications in biomedicine and healthcare.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.487-492
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• 2008

Facial expression recognition is an intensive research area for designing Human Computer Interfaces. In this work, we present a new facial expression recognition system utilizing Enhanced Independent Component Analysis (EICA) for feature extraction and discrete Hidden Markov Model (HMM) for recognition. Our proposed approach for the first time deals with sequential images of emotion-specific facial data analyzed with EICA and recognized with HMM. Performance of our proposed system has been compared to the conventional approaches where Principal and Independent Component Analysis are utilized for feature extraction. Our preliminary results show that our proposed algorithm produces improved recognition rates in comparison to previous works.

• Journal of Biomedical Engineering Research
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• v.34 no.2
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• pp.47-54
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• 2013

Electrical stimulation is delivered to auditory nerve (AN) through the electrodes in cochlear implant system. Neurogram is a spectrogram that includes information of neural response to electrical stimulation. We hypothesized that the similarity between a neurogram and an input-sound spectrogram could show how well a cochlear implant system works. In this study, we evaluated electrical stimulus configuration of CIS strategy using the computational model. The computational model includes stochastic property and anatomical features of cat auditory nerve fiber. To evaluate similarity between a neurogram and an input-sound spectrogram, we calculated Structural Similarity Index (SSIM). The results show that the dynamic range and the stimulation rate per channel influenced SSIM. Finally, we suggested the optimal configuration within the given stimulus CIS. We expect that the results and the evaluating procedure could be employed to improve the performance of a cochlear implant system.