• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.4
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• pp.765-771
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• 2009

The medical informatics for clustering Sasang types with collected clinical data is important for the personalized medicine, but it has not been thoroughly studied yet. The purpose of this study was to examine the usefulness of neural network data mining algorithm for traditional Korean medicine. We used Kohonen neural network, the Self-Organizing Map (SOM), for the analysis of biomedical information following data pre-processing and calculated the validity index as percentage correctly predicted and type-specific sensitivity. We can extract 12 data fields from 30 after data pre-processing with correlation analysis and latent functional relationship analysis. The profile of Myers-Briggs Type Inidcator and Bio-Impedance Analysis data which are clustered with SOM was similar to that of original measurements. The percentage correctly predicted was 56%, and sensitivity for So-Yang, Tae-Eum and So-Eum type were 56%, 48%, and 61%, respectively. This study showed that the neural network algorithm for clustering Sasang types based on clinical data is useful for the sasang type diagnostic test itself. We discussed the importance of data pre-processing and clustering algorithm for the validity of medical devices in traditional Korean medicine.

• Journal of Biomedical Engineering Research
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• v.32 no.2
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• pp.134-143
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• 2011

The selection of meaningful clinical tests and its reference values from a high-dimensional clinical data with imbalanced class distribution, one class is represented by a large number of examples while the other is represented by only a few, is an important issue for differential diagnosis between similar diseases, but difficult. For this purpose, this study introduces methods based on the concepts of both discernibility matrix and function in rough set theory (RST) with two discretization approaches, equal width and frequency discretization. Here these discretization approaches are used to define the reference values for clinical tests, and the discernibility matrix and function are used to extract a subset of significant clinical tests from the translated nominal attribute values. To show its applicability in the differential diagnosis problem, we have applied it to extract the significant clinical tests and its reference values between normal (N = 351) and abnormal group (N = 101) with either cholecystitis or cholelithiasis disease. In addition, we investigated not only the selected significant clinical tests and the variations of its reference values, but also the average predictive accuracies on four evaluation criteria, i.e., accuracy, sensitivity, specificity, and geometric mean, during l0-fold cross validation. From the experimental results, we confirmed that two discretization approaches based rough set approximation methods with relative frequency give better results than those with absolute frequency, in the evaluation criteria (i.e., average geometric mean). Thus it shows that the prediction model using relative frequency can be used effectively in classification and prediction problems of the clinical data with imbalanced class distribution.

• Journal of Biomedical Engineering Research
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• v.44 no.2
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• pp.139-146
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• 2023

Osteoporosis is a disease in which the risk of bone fractures increases due to a decrease in bone density caused by aging. Osteoporosis is diagnosed by measuring bone density in the total hip, femoral neck, and lumbar spine. To accurately measure bone density in the lumbar spine, the vertebral region must be segmented from the lumbar X-ray image. Deep learning-based automatic spinal segmentation methods can provide fast and precise information about the vertebral region. In this study, we used 695 lumbar spine images as training and test datasets for a deep learning segmentation model. We proposed a lumbar automatic segmentation model, CM-Net, which combines the center point of the spine and the modified U-Net network. As a result, the average Dice Similarity Coefficient(DSC) was 0.974, precision was 0.916, recall was 0.906, accuracy was 0.998, and Area under the Precision-Recall Curve (AUPRC) was 0.912. This study demonstrates a high-performance automatic segmentation model for lumbar X-ray images, which overcomes noise such as spinal fractures and implants. Furthermore, we can perform accurate measurement of bone density on lumbar X-ray images using an automatic segmentation methodology for the spine, which can prevent the risk of compression fractures at an early stage and improve the accuracy and efficiency of osteoporosis diagnosis.

• Genomics & Informatics
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• v.15 no.4
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• pp.123-127
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• 2017

Synonymous sites are generally considered to be functionally neutral. However, there are recent contradictory findings suggesting that synonymous alleles might have functional roles in various molecular aspects. For instance, a recent study demonstrated that synonymous single nucleotide polymorphisms have a similar effect size as nonsynonymous single nucleotide polymorphisms in human disease association studies. Researchers have recognized synonymous codon usage bias (SCUB) in the genomes of almost all species and have investigated whether SCUB is due to random nucleotide compositional bias or to natural selection of any functional exposure generated by synonymous mutations. One of the most prominent observations on the non-neutrality of synonymous codons is the correlation between SCUB and levels of gene expression, such that highly expressed genes tend to have a higher preference toward so-called optimal codons than lowly expressed genes. In relation, it is known that amounts of cognate tRNAs that bind to optimal codons are significantly higher than the amounts of cognate tRNAs that bind to non-optimal codons in genomes. In the present paper, we review various functions that synonymous codons might have other than regulating expression levels.

• Journal of Biomedical Engineering Research
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• v.27 no.6
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• pp.409-417
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• 2006

Research on neural circuit is a difficult area due to complexity and inaccessibility. Due to recent developments, the research using multi-electrode array of cells or tissues has become an important research area. However, there are some difficulties to decode the submerged meaning from huge and complex neural data. Moreover, it needs a harmonic collaboration between informatics and bioscience. In this paper, we have developed a custom-designed signal processing technique for multi-electrode array measured neural responses induced by electrical stimuli to the hippocampal tissue slices of the rat brain. The raw data from hippocampal slice using the multi-electrode array system were saved in a computer. Then we estimated characteristic points in each channel and calculated the total activity. To estimate the points, we used the Polynomial Fitting Approximation Method. Using the calculated total activity, we could provide the histogram or pseudo-image matrix to help interpretation of results.

• Genomics & Informatics
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• v.17 no.3
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• pp.29.1-29.8
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• 2019

The Wellcome Trust Case Control Consortium (WTCCC) study was a large genome-wide association study that aimed to identify common variants associated with seven diseases. That study combined two control datasets (58C and UK Blood Services) as shared controls. Prior to using the combined controls, the WTCCC performed analyses to show that the genomic content of the control datasets was not significantly different. Recently, the analysis of human leukocyte antigen (HLA) genes has become prevalent due to the development of HLA imputation technology. In this project, we extended the between-control homogeneity analysis of the WTCCC to HLA. We imputed HLA information in the WTCCC control dataset and showed that the HLA content was not significantly different between the two control datasets, suggesting that the combined controls can be used as controls for HLA fine-mapping analysis based on HLA imputation.

• Genomics & Informatics
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• v.14 no.2
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• pp.46-52
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• 2016

Diverse somatic mutations have been reported to serve as cancer drivers. Recently, it has also been reported that epigenetic regulation is closely related to cancer development. However, the effect of epigenetic changes on cancer is still elusive. In this study, we analyzed DNA methylation data on colon cancer taken from The Caner Genome Atlas. We found that several promoters were significantly hypermethylated in colon cancer patients. Through clustering analysis of differentially methylated DNA regions, we were able to define subgroups of patients and observed clinical features associated with each subgroup. In addition, we analyzed the functional ontology of aberrantly methylated genes and identified the G-protein-coupled receptor signaling pathway as one of the major pathways affected epigenetically. In conclusion, our analysis shows the possibility of characterizing the clinical features of colon cancer subgroups based on DNA methylation patterns and provides lists of important genes and pathways possibly involved in colon cancer development.

• Genomics & Informatics
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• v.17 no.1
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• pp.9.1-9.5
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• 2019

In previous studies, we demonstrated that some sites in the first intron likely regulate gene expression. In the present work, we sought to further confirm the functional relevance of first intron sites by estimating the quantity of rare alleles in the first intron. A basic hypothesis posited herein is that genomic regions carrying more functionally important sites will have a higher proportion of rare alleles. We estimated the proportions of rare single nucleotide polymorphisms with a minor allele frequency < 0.01 located in several histone marks in the first introns of various genes, and compared them with those in other introns and those in 2-kb upstream regions. As expected, rare alleles were found to be significantly enriched in most of the regulatory sites located in the first introns. Meanwhile, transcription factor binding sites were significantly more enriched in the 2-kb upstream regions (i.e., the regions of putative promoters of genes) than in the first introns. These results strongly support our proposal that the first intron sites of genes may have important regulatory functions in gene expression independent of promoters.

• Journal of Photoscience
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• v.9 no.2
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• pp.509-511
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• 2002

In this study, we investigated apoptotic cell death induced by photodynamic therapy using 5-aminolaevulinic acid (ALA-PDT) in human promyelocytic leukemia cells (HL-60). ALA-PDT induced apoptosis in HL-60 cells as confirmed by DNA agarose gel electrophoresis and nuclear staining with Hoechst 33342. The apoptotic cell death was inhibited by addition of broad-spectrum caspase inhibitor Z-Asp-CH$_2$-DCB, indicating that the apoptotic cell death was induced in a caspase-dependent manner. Actually, western blotting analysis revealed that caspase-3 was processed as early as 1.5 h after ALA-PDT. Cytoplasmic cytochrome c released from mitochondria was detected by western blotting. However, inhibitor of caspase-9, a cysteine protease located in the downstream of cytochrome c release, was not able to reduce the apoptotic cell death. Therefore, the mitochondrial apoptotic pathway was not involved in the ALA-PDT-induced apoptosis. On the other hand, it was found that ALA-PDT-induced apoptosis was clearly inhibited by pretreatment of caspase-8 inhibitor. These data suggest that caspase-8-mediated apoptotic pathway is important in ALA-PDT-induced cell death.

• Genomics & Informatics
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• v.18 no.2
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• pp.21.1-21.7
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• 2020

Scientific research is mostly published in English, regardless of the researcher's nationality. However, this growing practice impairs or hinders the comprehension of professionals who depend on the results of these studies to provide adequate care for their patients. We suggest that machine translation (MT) can be used as a way of providing useful translation for biomedical articles, even though the translation itself may not be fluent. To tackle possible mistranslation that can harm a patient, we resort to crowd-sourced validation of translations. We developed a prototype of MT validation and edition, where users can vote for that translation as valid, or suggest modifications (i.e., post-editing the MT). A glossary match system is also included, aiming at terminology consistency.