• 스마트미디어저널
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• 제12권7호
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• pp.52-58
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• 2023

Alzheimer's disease is one type of dementia, the symptoms can be treated by detecting the disease at its early stages. Recently, many computer-aided diagnosis using magnetic resonance image(MRI) have shown a good results in the classification of AD. Taken these MRI images and feed to Free surfer software to extra the features. In consideration, using T1-weighted images and classifying using the convolution neural network (CNN) model are proposed. In this paper, taking the subjects from ADNI of subcortical and cortical features of 190 subjects. Consider the study to reduce the complexity of the model by using the single layer in the Res-Net, VGG, and Alex Net. Multi-class classification is used to classify four different stages, CN, EMCI, LMCI, AD. The following experiment shows for respective classification Res-Net, VGG, and Alex Net with the best accuracy with VGG at 96%, Res-Net, GoogLeNet and Alex Net at 91%, 93% and 89% respectively.

• 사상체질의학회지
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• 제23권1호
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• pp.24-32
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• 2011

1. Objectives: This research was proposed to reinterpret "Soeumin Bumron(少陰人 泛論)"through development of Soeumin exterior disease in Sasang Constitutional Medicine(SCM). 2. Methods: We chronically compared the conceptions, symptoms, mechanisms and treatments of Soeumin exterior disease from "Donguisusebowon-GabObon(東醫壽世保元甲午本)"(DGO) to " "Donguisusebowon-ShinChukbon(東醫壽世保元辛丑本)"(DSC) 3. Results and Conclusions: (1) The classification standard of Soeumin exterior disease was different in DGO and DSC. (2) Soeumin exterior disease classified Taeyang Disease(太陽病), Yangmyoung Disease(陽明病) in DGO and Ulkwang-syndrome(鬱狂證), Mangyang-syndrome(亡陽證) in DSC. (3) Based on the changes of understanding about Soeumin exterior disease from DGO to DSC, we attempted to reinterpret "Soeumin Bumron(少陰人 泛論)" in view of DSC. In view of DSC, the classification standard of Soeumin exterior disease focused on Warm Yang Qi(陽煖之氣), Healthy energy(保命之主) of Soeumin.

• Journal of Acupuncture Research
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• 제33권1호
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• pp.69-77
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• 2016

Objectives : The objective of this study is to review external approaches using acupuncture and related treatments of hyperpigmentation disorders and their classification in traditional medicine. Methods and Results : Hyperpigmentation was recorded for the first time in Treatise on the Pathogenesis and Manifestations of All Diseases published in 610 A.D. This suggests that the symptom has already been recognized as an independent disease in East Asia for more than 1,400 years. Over the course of several centuries, there has been a significant evolution in the traditional treatments for hyperpigmentation. There are many different types of therapy, including body acupuncture, intradermal acupuncture, ear acupuncture, ear acupressure, blood-letting treatment, pharmacopuncture, plum-blossom needle therapy, burning acupuncture therapy, moxibustion, and guasha. In addition, the traditional classification of hyperpigmentation has been changing shape. However, no attempts have been made to establish the academic linkage between the modern classification of hyperpigmentation disorders and the traditional one, on account of different concepts and names of the ailment. This study was designed in an attempt to identify the linkage of the categorization of the Korean Standard Classification of Disease (KCD) and the traditional classification. Conclusions : Through this literature review, we found that there has been a significant evolution in the treatment of hyperpigmentation disorders in East Asia. Traditional medical treatment for skin disease, including hyperpigmentation, is expected to be further developed with the advancement of science and technology.

• 대한세포병리학회지
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• 제5권2호
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• pp.106-112
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• 1994

Fine needle aspiration biopsy has been proved as a safe, accurate and cost-effective diagnostic modality in palpable breast lesions. Cytologically, fibrocystic disease can be classified into 3 categories as nonproliferative breast disease, proliferative breast disease without atypia, and proliferative breast disease with atypia. This terminology for fine needle aspirates is compatible with that of diagnostic histopathology. Cytologic differentiation of nonproliferative disease from proliferative breast disease is important, since the risk of cancer development in cases of atypical hyperplasia is 4-5 times higher than that of general population. Twenty five fine needle aspirates of fibrocystic disease confirmed by subsequent histopathology were re-evaluated and classified into 3 categories depending on their architectural and nuclear features. In addition, these aspirates were scored according to the cytologic grading system, devised by Masood et al. and based on six cytologic criteria. Concordance rates between cytomorpholgic diagnosis and cytologic diagnosis using the cytologic criteria grading system and histologic diagnosis were 88% and 92%, respectively.

• 대한중풍순환신경학회지
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• 제13권1호
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• pp.52-62
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• 2012

Object : The aim of this study was to examine the differences of symptom improvement between different diagnosis classification groups in acute cerebral infarction patients. Methods : We studied inpatients within a month after the onset of cerebral infarction who were admitted at Kyunghee University Oriental Medical Center from May 2011 to October 2012. We compared the improvement of Motricity Index and Scandinavian Stroke Scale score between Fire-heat group(n=20), Yin deficiency group(n=31), Dampness-phlegm group(n=30), and Qi deficiency group(n=13). Results : Yin deficiency group patients with cerebral infarction showed the most improvement in MI and SSS scores, and patients in Fire-heat group showed the poorest improvement in MI and SSS scores. There was a significant difference between the two groups, but there were no significant differences between all four diagnosis classification groups. Conclusions : This study provides evidence that diagnosis classification could be considered as an important factor in predicting the prognosis of acute cerebral infarction.

• Journal of Biosystems Engineering
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• 제40권4호
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• pp.417-427
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• 2015

Purpose: This study investigated different band selection methods to classify spectrally similar data - obtained from aerial images of healthy citrus canopies and citrus greening disease (Huanglongbing or HLB) infected canopies - using small differences without unmixing endmember components and therefore without the need for an endmember library. However, large number of hyperspectral bands has high redundancy which had to be reduced through band selection. The objective, therefore, was to first select the best set of bands and then detect citrus Huanglongbing infected canopies using these bands in aerial hyperspectral images. Methods: The forward feature selection algorithm (FFSA) was chosen for band selection. The selected bands were used for identifying HLB infected pixels using various classifiers such as K nearest neighbor (KNN), support vector machine (SVM), naïve Bayesian classifier (NBC), and generalized local discriminant bases (LDB). All bands were also utilized to compare results. Results: It was determined that a few well-chosen bands yielded much better results than when all bands were chosen, and brought the classification results on par with standard hyperspectral classification techniques such as spectral angle mapper (SAM) and mixture tuned matched filtering (MTMF). Median detection accuracies ranged from 66-80%, which showed great potential toward rapid detection of the disease. Conclusions: Among the methods investigated, a support vector machine classifier combined with the forward feature selection algorithm yielded the best results.

• Journal of Forest and Environmental Science
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• 제32권4호
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• pp.384-391
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• 2016

In this study, regions infected by pine wilt disease were extracted by using object-based classification method (OB-infected region), and the characteristics of special distribution about OB-infected region were figured out. Scale 24, Shape 0.1, Color 0.9, Compactness 0.5, and Smoothness 0.5 was selected as the objected-based, optimal weighted value of OB-infected region classification. The total accuracy of classification was high with 99% and Kappa coefficient was also high with 0.97. The area of OB-infected region was approximately 90 ha, 16% of the total area. The OB-infected region in Age class V and VI was intensively distributed with 97% of the total. Also, The OB-infected region in Middle and Large DBH class was intensively distributed with 99% of the total. In terms of the topographic characteristics of OB-infected region, the damages occurred approximately 86% below the altitude of 200 m, and occurred 91% with a slope less than 10 degree. The damage occurred a lot in low hilly mountain and undulating slope. In addition, the accessibility to road and residential area from OB-infected region was less than 300 m in large part. Overall, it was figured out that artificial effect is stronger than natural effect with regard to the spread of pine wilt disease.

• 한국멀티미디어학회논문지
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• 제24권5호
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• pp.667-675
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• 2021

The treatments for symptoms of Alzheimer's disease are being provided and for the early diagnosis several researches are undergoing. In this regard, by using T1-weighted images several classification techniques had been proposed to distinguish among AD, MCI, and Healthy Control (HC) patients. In this paper, we also used some traditional Machine Learning (ML) approaches in order to diagnose the AD. This paper consists of an improvised feature selection method which is used to reduce the model complexity which accounted an issue while utilizing the ML approaches. In our presented work, combination of subcortical and cortical features of 308 subjects of ADNI dataset has been used to diagnose AD using structural magnetic resonance (sMRI) images. Three classification experiments were performed: binary classification. i.e., AD vs eMCI, AD vs lMCI, and AD vs HC. Proposed Feature Selection method consist of a combination of Principal Component Analysis and Recursive Feature Elimination method that has been used to reduce the dimension size and selection of best features simultaneously. Experiment on the dataset demonstrated that SVM is best suited for the AD vs lMCI, AD vs HC, and AD vs eMCI classification with the accuracy of 95.83%, 97.83%, and 97.87% respectively.

• Journal of Multimedia Information System
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• 제8권4호
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• pp.233-242
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• 2021

Various anatomical MRI imaging biomarkers for Alzheimer's Disease (AD) identification have been recognized so far. Cortical and subcortical volume, hippocampal, amygdala volume, and genetics patterns have been utilized successfully to diagnose AD patients from healthy. These fundamental sMRI bio-measures have been utilized frequently and independently. The entire possibility of anatomical MRI imaging measures for AD diagnosis might thus still to analyze fully. Thus, in this paper, we merge different structural MRI imaging biomarkers to intensify diagnostic classification and analysis of Alzheimer's. For 54 clinically pronounce Alzheimer's patients, 58 cognitively healthy controls, and 99 Mild Cognitive Impairment (MCI); we calculated 1. Cortical and subcortical features, 2. The hippocampal subfield, amygdala nuclei volume using Freesurfer (6.0.0) and 3. Genetics (APoE ε4) biomarkers were obtained from the ADNI database. These three measures were first applied separately and then combined to predict the AD. After feature combination, we utilize the sequential feature selection [SFS (wrapper)] method to select the top-ranked features vectors and feed them into the Multi-Kernel SVM for classification. This diagnostic classification algorithm yields 94.33% of accuracy, 95.40% of sensitivity, 96.50% of specificity with 94.30% of AUC for AD/HC; for AD/MCI propose method obtained 85.58% of accuracy, 95.73% of sensitivity, and 87.30% of specificity along with 91.48% of AUC. Similarly, for HC/MCI, we obtained 89.77% of accuracy, 96.15% of sensitivity, and 87.35% of specificity with 92.55% of AUC. We also presented the performance comparison of the proposed method with KNN classifiers.

• 사상체질의학회지
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• 제11권1호
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• pp.119-135
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• 1999

본 연구(硏究)는 1996.3월(月)에서 1998.11월(月)사이에 동의대학교(東義大學校) 한의과대학(韓醫科大學) 부속한방병원(附屬韓方病院)에 내원(來院) 가료중(加療中) 환자(患者) 196명을 대상(對象)으로 하였으며 사상체질(四象體質)의 판별(判別)은 사상변증내용(四象辨證內容) 설문조사지(設問調査紙)(I)과 사상체질분류검사(象體質分類檢査)(QSCCII)를 중심으로 하였다. 본 결과는 사상체질(四象體質)과 질병(疾病) 및 증상유형(症狀類形)에 대한 설문지(說問紙)를 비교하여 얻은 것이다. 1. 태음인(太陰인)은 체중증가(體重增加), 땀이 많이 난다. 몸이 붓는다. 허리가 아프다는 증상(症狀)과 기름진 음식(飮食)을 잘 먹으며 음식(飮食)을 짜게 먹는 편이 다른 체질(體質)에 비하여 더욱 유발(頻發)하였다. 2. 소음인(少陰인)은 안색이 나쁘다. 목의 이물감, 수면장애(睡眠障碍) 식욕감퇴(食慾減退), 쉽게 피로(疲勞)해짐, 식사(食事)와 무관한 위(胃)의 통증(痛症), 두통(頭痛), 생리통증상(生理痛症狀)과 기름진 음식(飮食)을 잘 안 먹는다. 음식(飮食)을 싱겁게 먹는 편이 다른 체질(體質)에 비하여 더욱 유발(頻發)하였다. 3. 통계적(統計的)으로 유의성(有意性)을 가지지는 못하였지만, 소양인(少陽人)은 호흡기계질환(呼吸器系疾患)에서 단순한 기침증상(症狀) 근골격계질환(筋骨格系疾患)에서 관절(關節)의 운동장애(運動障碍), 부인과계(歸人科系)에서 월경(月經)의 조기(調期)와 양(量)의 변화(變化)와 생식기(生殖器) 소양증(搔痒症), 피부계(皮膚系)에서 가려움증과 부스럼증 등은 다른 체질(體質)에 비하여 비교적 많았고 심혈관계질환(心血管系疾患), 혈액계질환(血液系疾患)은 비교적 적었다. 소음인(少陰人)은 전반적(全般的)인 소화기계질환(消化器系疾患), 호흡기계질환(呼吸器系疾患)에서 인흡(咽吸)의 이물감 통증, 심혈관계질환(心血管系疾患), 혈액계질환(血液系疾患), 근골격계질환(筋骨格系疾患)에서 통증(痛症)이나 비증(痺症), 정신신경계질환(精神神經系疾患)에서 정신계질환(精神系疾患), 부인과계(婦人科系)에서 월경통(月經痛)을 비롯한 유방(乳房)의 몽우리 냉증(冷症), 피부계(皮膚系)에서 발진(發疹)이나 두드러기, 시각계질환(視覺系疾患)과 청각계질환(聽覺系疾患)등이 다른 체질(體質)에 비해 많았다. 태음인(太陰人) 호흡기계질환(呼吸器系疾患)에서 목이 잘 쉬는 증상, 근골격계질환(筋骨格系疾患)에서 요통(腰痛), 정신신경계질환(精神神經系疾患)에서 신경계질환(神經系疾患), 피부계(皮膚系)에서 발진(發疹)이나 두드러기등이 다른 체질(體質)에 비하여 다소 많았으며 부인과계질환(婦人科系疾患)은 적었다.