• Journal of Digital Contents Society
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• v.17 no.6
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• pp.565-579
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• 2016

In this paper a novel cancer subtype's classifier based on Hybrid Samples Balanced Genetic Algorithm with Extreme Learning Machine (hSBGA-ELM) is presented. Proposed cancer subtype's classifier uses genes' expression data of 16063 genes from open Global Cancer Map (GCM) data base for accurate cancer subtype's classification. Proposed method efficiently classifies 14 subtypes of cancer (breast, prostate, lung, colorectal, lymphoma, bladder, melanoma, uterus, leukemia, renal, pancreas, ovary, mesothelioma and CNS). Proposed hSBGA-ELM unifies genes' selection procedure and cancer subtype's classification into one framework. Proposed Hybrid Samples Balanced Genetic Algorithm searches a reduced robust set of genes responsible for cancer subtype's classification from 16063 genes available in GCM data base. Selected reduced set of genes is used to build cancer subtype's classifier using Extreme Learning Machine (ELM). As a result, reduced set of robust genes guarantees stable generalization performance of the proposed cancer subtype's classifier. Proposed hSBGA-ELM discovers 95 genes probably responsible for cancer. Comparison with existing cancer subtype's classifiers clear indicates efficiency of the proposed method.

• Phonetics and Speech Sciences
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• v.14 no.2
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• pp.87-99
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• 2022

A review regarding indicators used in Korean research is needed to develop a diagnostic marker system for Korean children with speech sound disorders (SSD). This literature review examined the research conducted to reveal the characteristics of children with SSD of unknown origin in Korea. The researchers in Korea used diverse variables as indicators to identify the natures of children with SSD. These included indicators related to external characteristics of speech sound and comorbid features other than external aspects of speech sound. The attention has been focused on specific indicators so far. This result implies that some indicators may still require closer study in various aspects due to their influence, and some may require more attention due to the limited number of research. This article argues that more research is necessary to comprehensively describe the unique characteristics of children with SSD of unknown origin and suggests a direction for future research regarding diagnostic markers and subtype classification of SSD. It also proposes potential diagnostic markers and a set of assessments for the subtype classification of SSD.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.175-177
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• 2003

This paper addresses a problem of classifying human breast cancer into its subtypes. A main ingredient in our approach is kernel machines such as support vector machine (SVM). kernel principal component analysis (KPCA). and kernel partial least squares (KPLS). In the task of breast cancer classification, we employ both SVM and KPLS and compare their results. In addition to this classification. we also analyze the patterns of clinical outcomes in the feature space. In order to visualize the clinical outcomes in low-dimensional space, both KPCA and KPLS are used. It turns out that these methods are useful to identify correlations between clinical outcomes and the nonlinearly protected expression profiles in low-dimensional feature space.

• Journal of Periodontal and Implant Science
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• v.53 no.6
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• pp.453-466
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• 2023

Purpose: This study aimed to quantify alveolar bone morphology, demonstrate the relationship between tooth angulation and alveolar bone thickness, and introduce a new classification for anterior mandibular teeth related to immediate implant placement (IIP). Methods: Cone-beam computed tomography (CBCT) images of 211 anterior mandibular teeth were analyzed in sagittal slices to measure the thickness of the facial alveolar bone crest (FAB1) and apex (FAB2), and the lingual alveolar bone crest (LAB1) and apex (LAB2). Tooth angulation was classified as 1°-10°, 11°-20°, and >20° according to the tooth's long axis and alveolar bone wall. Spearman correlation coefficients were used to evaluate correlations between the variables. Results: FAB1 and LAB1 were predominantly thin (<1 mm) (84.4% and 73.4%, respectively), with the lateral incisors being thinnest. At the apical level, FAB2 and LAB2 were thick in 99.5% and 99.1% of cases, respectively. Significant differences were documented in FAB2 (P=0.004), LAB1 (P=0.001), and LAB2 (P=0.001) of all mandibular teeth. At all apical levels of the inspected teeth, a significant negative correlation existed between TA and FAB2. Meanwhile, TA showed a significant positive correlation with LAB2 of the lateral incisors and canines. These patterns were then divided into class I (thick facial and lingual alveolar bone), class II (facially inclined teeth) with subtype A (1°-10°) and subtype B (11°-20°), and class III (lingually inclined teeth) with subtype A (1°-10°) and subtype B (11°-20°). Conclusions: Mandibular anterior teeth have predominantly thin facial and lingual crests, making the lingual bone apical thickness crucial for IIP. Although anchorage can be obtained from lingual bone, tooth angulation and tooth types had an impact on IIP planning. Hence, the new classification based on TA and alveolar bone wall may enable rational clinical planning for IIP treatment.

• Journal of Yeungnam Medical Science
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• v.28 no.1
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• pp.1-12
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• 2011

Primary liver carcinomas have classified classified into hepatocellular carcinoma, cholangiocarcinoma, and combined hepatocellular-cholangiocarcinoma (CHC). CHC is a tumor containing unequivocal, intimately mixed elements of both hepatocellular carcinoma and cholangiocarcinoma. It forms a small but significant proportion of primary liver carcinomas. The origin and pathogenesis of CHC have not been well established. According to the 2010 WHO classification, CHCs are categorized into 2 groups: the classical type and a subtype with stem cell features. This review describes recent progress in pathology and classification of CHC.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1172-1180
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• 2004

Recently, the gene expression data, product of high-throughput technology, appeared in earnest and the studies related with it (so-called bioinformatics) occupied an important position in the field of biological and medical research. The microarray is a revolutionary technology which enables us to monitor several thousands of genes simultaneously and thus to gain an insight into the phenomena in the human body (e.g. the mechanism of cancer progression) at the molecular level. To obtain useful information from such gene expression measurements, it is essential to analyze the data with appropriate techniques. However the high-dimensionality of the data can bring about some problems such as curse of dimensionality and singularity problem of matrix computation, and hence makes it difficult to apply conventional data analysis methods. Therefore, the development of method which can effectively treat the data becomes a challenging issue in the field of computational biology. This research focuses on the gene selection and classification for cancer subtype discrimination based on gene expression (microarray) data.

• Journal of Physiology & Pathology in Korean Medicine
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• v.21 no.1
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• pp.263-269
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• 2007

In Korea, Korean Medicine is the first choice in treating stroke. Because stroke prognosis, risk of recurrence, and choices for management are influenced by stroke subtype, correct analysis of stroke subtype is important. Until now, the studies on differentiation of the symptoms and signs for the stroke were a few and the Korean standard differentiation of the symptoms and signs for the stroke don't exist. To develop the Korean standard differentiation of the symptoms and signs for the stroke, we go through subtype of stroke in traditional chinese medicine, Korean Medicine, western medicine.

• BMB Reports
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• v.57 no.3
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• pp.125-134
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• 2024

Whole-genome doubling (WGD), characterized by the duplication of an entire set of chromosomes, is commonly observed in various tumors, occurring in approximately 30-40% of patients with different cancer types. The effect of WGD on tumorigenesis varies depending on the context, either promoting or suppressing tumor progression. Recent advances in genomic technologies and large-scale clinical investigations have led to the identification of the complex patterns of genomic alterations underlying WGD and their functional consequences on tumorigenesis progression and prognosis. Our comprehensive review aims to summarize the causes and effects of WGD on tumorigenesis, highlighting its dualistic influence on cancer cells. We then introduce recent findings on WGD-associated molecular signatures and genetic aberrations and a novel subtype related to WGD. Finally, we discuss the clinical implications of WGD in cancer subtype classification and future therapeutic interventions. Overall, a comprehensive understanding of WGD in cancer biology is crucial to unraveling its complex role in tumorigenesis and identifying novel therapeutic strategies.

• Journal of Chest Surgery
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• v.37 no.8
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• pp.684-690
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• 2004

Background: Primary thymic epithelial neoplasm is a type of mediastinal tumors that have various biologic and morphologic features. In this study, we reclassified 59 cases of thymic epithelial tumors by the new WHO classification. We inquired whether the new WHO classification has independent prognostic relevance by analyzing clinical characteristics of thymic epithelial tumors including Masaoka's clinical stage. Material and Method: From December 1986 to August 2003, 59. patients who underwent surgery in the Keimyung University Dongsan Medical Center with definite diagnosis of thymic epithelial tumor were studied. We analyzed the histologic subtype (WHO classification). clinical stage (Masaoka's clinical stage) and patient's characteristics (sex, age, myasthenia gravis, tumor size, invasion. recurrence, metastasis) as prognostic factors. We analyzed the relationship between histologic subtype and clinical stage. Result: 32 patients were male and 27 were female. Mean age was 50.1$\pm$14.2. From WHO A to C, all thymic epithelial tumors were reclassified by the new WHO classification. Six patients (10.2%) had Type A, 7 (11.9%) had Type AB, 7 (11.9%) had Type B$_1$, 10 (16.9%) had Type B$_2$ and 7 (11.9%) had Type B$_3$, 22 (37.3%) had Type C. Two factors were shown by multivariate analysis to be associated with a favorable prognosis: completeness of resection (p=0.003) and non-invasiveness (p=0.001). The overall 5-year survival of the 59 patients was 53%, subtype A and AB were 92.3%, B$_1$ and B$_2$ were 70.2%, and B$_3$ and C were 26.1%. The association between histologic subtype and invasive behavior (stage) was statistically significant (p<0.001). Conclusion: The WHO classfication is not only a histologic classfication of the thymic epithelial tumors but also a significant prognostic factor that influence the survival of thymic epithelial tumors.

• Genomics & Informatics
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• v.18 no.4
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• pp.35.1-35.7
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• 2020

Identifying the patterns of gene expression in breast cancers is essential to understanding their pathophysiology and developing anticancer drugs. Breast cancer is a heterogeneous disease with different subtypes determined by distinct biological features. Luminal breast cancer is characterized by a relatively high expression of estrogen receptor (ER) and progesterone receptor (PR) genes, which are expressed in breast luminal cells. In ~25% of invasive breast cancers, human epidermal growth factor receptor 2 (HER2) is overexpressed; these cancers are categorized as the HER2 type. Triple-negative breast cancer (TNBC), in which the cancer cells do not express ER/PR or HER2, shows highly aggressive clinical outcomes. TNBC can be further classified into specific subtypes according to genomic mutations and cancer immunogenicity. Herein, we discuss the brief history of TNBC classification and its implications for promising treatments.