• 스마트미디어저널
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• 제12권3호
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• pp.30-37
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• 2023

Alzheimer's disease (AD) symptoms are being treated by early diagnosis, where we can only slow the symptoms and research is still undergoing. In consideration, using T1-weighted images several classification models are proposed in Machine learning to identify AD. In this paper, we consider the improvised feature selection, to reduce the complexity by using wrapping techniques and Restricted Boltzmann Machine (RBM). This present work used the subcortical and cortical features of 278 subjects from the ADNI dataset to identify AD and sMRI. Multi-class classification is used for the experiment i.e., AD, EMCI, LMCI, HC. The proposed feature selection consists of Forward feature selection, Backward feature selection, and Combined PCA & RBM. Forward and backward feature selection methods use an iterative method starting being no features in the forward feature selection and backward feature selection with all features included in the technique. PCA is used to reduce the dimensions and RBM is used to select the best feature without interpreting the features. We have compared the three models with PCA to analysis. The following experiment shows that combined PCA &RBM, and backward feature selection give the best accuracy with respective classification model RF i.e., 88.65, 88.56% respectively.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2022년도 추계학술발표대회
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• pp.541-543
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• 2022

In recent years, retinal disorders have become a serious health concern. Retinal disorders develop slowly and without obvious signs. To avoid vision deterioration, early detection and treatment are critical. Optical coherence tomography (OCT) is a non-invasive and non-contact medical imaging technique used to acquire informative and high-resolution image of retinal area and underlying layers. Disease signs are difficult to detect because OCT images have many areas which are not related to any disease. In this paper, we present a deep learning-based method to perform multi-label classification on a long-tailed OCT dataset. Our method first extracts the region of interest and then performs the classification task. We achieve 98% accuracy, 92% sensitivity, and 99% specificity on our private OCT dataset. Using the heatmap generated from trained convolutional neural network, our method is more robust and explainable than previous approaches because it focuses on areas that contain disease signs.

• International Journal of Computer Science & Network Security
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• 제24권1호
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• pp.119-126
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• 2024

Disease caused by the coronavirus (COVID-19) is sweeping the globe. There are numerous methods for identifying this disease using a chest imaging. Computerized Tomography (CT) chest scans are used in this study to detect COVID-19 disease using a pretrain Convolutional Neural Network (CNN) ResNet50. This model is based on image dataset taken from two hospitals and used to identify Covid-19 illnesses. The pre-train CNN (ResNet50) architecture was used for feature extraction, and then fully connected layers were used for classification, yielding 97%, 96%, 96%, 96% for accuracy, precision, recall, and F1-score, respectively. When combining the feature extraction techniques with the Back Propagation Neural Network (BPNN), it produced accuracy, precision, recall, and F1-scores of 92.5%, 83%, 92%, and 87.3%. In our suggested approach, we use a preprocessing phase to improve accuracy. The image was enhanced using the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm, which was followed by cropping the image before feature extraction with ResNet50. Finally, a fully connected layer was added for classification, with results of 99.1%, 98.7%, 99%, 98.8% in terms of accuracy, precision, recall, and F1-score.

• 한국정보통신학회논문지
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• 제20권11호
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• pp.2137-2142
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• 2016

심장에서 발생된 전류는 전위 뿐만 아니라 자기장을 생성한다. 본 논문에서는 61 채널 양자 간섭 장치 (SQUID) 시스템을 사용하여 심자도 (MCG)의 신호를 취득하고, 이것으로부터 임상적으로 유의하다고 생각되는 다양한 특징 파라미터를 계산한다. 이를 입력으로 신경회로망 알고리즘을 적용하여 허혈성 심장질환의 분류를 수행하였다. 심자도 신호는 전처리 과정을 통해 파라미터의 추출을 용이하게 하였다. 연구에 사용된 데이터는 정상인 10명과 안정형 협심 증세를 보이는 허혈성 심장질환 환자 10명분의 신호이다. 이들 신호로부터 임상적으로 유의한 특징점, 특징 간격 파라미터 및 진폭비를 추출하였다. 심자도 특징 파라미터를 신경회로망 입력으로 사용하여 허혈성 심장질환의 분류가 가능함을 보였다.

• 동의생리병리학회지
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• 제25권2호
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• pp.318-321
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• 2011

In this study, when a physician make a diagnosis of the Pattern Identifications(PIs) of stroke patients, the development methods of the PIs classification function is considered by diagnostic questionnaire of the PIs for stroke patients. Clinical data collected from 1,502 stroke patients who was identically diagnosed for the PIs subtypes diagnosed by two clinical experts with more than 3 years experiences in 13 oriental medical hospitals. In order to develop the classification function into PIs using the 44 items-Fire&heat(19), Qi-deficiency(11), Yin-deficiency(7), Dampness phlegm(7)- of them was significant statistically by univariate analysis in 61 questionnaires totally, we make some comparisons of the results of discriminant analysis model and generalized logit model. The overall diagnostic accuracy rate of the PIs subtypes for discriminant model(74.37%) was higher than 3% of generalized logit model(70.09%).

• 사상체질의학회지
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• 제8권1호
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• pp.337-347
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• 1996

동의대학교 한의과대학 부속한방병원에 내원한 76명을 대상으로 체질진단분류와 질병 및 증상유형과의 관계를 문진표 (19개 항목 123문항)를 중심으로 비교 분석하여 다음과 같은 결론을 얻었다. 1. 체중감소증상은 체질에 따라 유의한 차이가 있었고 태음인이 소양인이나 소음인에 비하여 더욱 빈발하였다. 2. 구토증상은 체질에 따라 유의한 차이가 있었고 태음인이 소양인이나 소음인에 비하여 더욱 빈발하였다. 3. 목이 쉬는 증상은 체질에 따라 유의한 차이가 있었고 소음인이 소양인이나 태음인에 비하여 더욱 빈발하였다. 4. 호흡곤란 증상은 체질에 따라 유의한 차이가 있었고 태음인이 소양인이나 소음인에 비하여 더욱 빈발하였다. 5. 관절통 증상은 체질에 따라 유의한 차이가 있었고 소양인이 소음인이나 태음인에 비하여 더욱 빈발하였다. 6. 생리통증상은 체질에 따라 유의한 차이가 있었고 소음인이 소양인이나 태음인에 비하여 더욱 빈발하였다. 7. 과거력은 체질에 따라 유의한 차이가 없었으며 다만 과거력은 나이에 따라 일부 유의한 차이가 있었을 뿐이다. 이상의 결과로 볼 때 체질과 각종 질병이나 증상유형에 대한 임상적인 연구가 더욱 필요할 것으로 사려된다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.709-711
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• 2003

The purpose of this study is to detect the damaged red pine trees by pine wilt disease using high resolution satellite image of IKONOS Geo. IKONOS images are segmented with eCognition image processing software. A segment based maximum likelihood classification was performed to delineate the pine stand. The pine stands are regarded as a potential damage area. In order to develop a methodology to detect the location of damaged trees from the high resolution satellite image, black and white aerial photographs were used as a simulated image. The developed method based on filtering technique. A local maximum filter was adapted to detect the location of individual tree. This report presents a part of the first year results of an ongoing project.

• Genomics & Informatics
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• 제2권1호
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• pp.19-29
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• 2004

Gene expression profiles may offer more information than morphology and provide an alternative to morphology- based tumor classification systems. Informative gene selection is finding gene subsets that are able to discriminate between tumor types, and may have clear biological interpretation. Gene selection is a fundamental issue in gene expression based tumor classification. In this report, techniques for selecting informative genes are illustrated and supervised shaving introduced as a gene selection method in the place of a clustering algorithm. The supervised shaving method showed good performance in gene selection and classification, even though it is a clustering algorithm. Almost selected genes are related to leukemia disease. The expression profiles of 3051 genes were analyzed in 27 acute lymphoblastic leukemia and 11 myeloid leukemia samples. Through these examples, the supervised shaving method has been shown to produce biologically significant genes of more than $94\%$ accuracy of classification. In this report, SVM has also been shown to be a practicable method for gene expression-based classification.

• 사상체질의학회지
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• 제23권1호
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• pp.63-78
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• 2011

1. Objectives: We aimed to propose a sub-classification system for the Taeeumin symptomatology by examining the Taeeumin pathology and symptomatology descriptions appearing in "Donguisusebowon". 2. Methods: The Gabo Edition and the Sinchuk Edition (the upgraded and revised edition) of "Donguisusebowon" were reviewed and examined for relevant information on the Taeeum pathology and symptomatology. 3. Results and Conclusions: 1) In the Taeeumin symptomatology, the Exterior disease develops from the basic pathology of Esophagus-Cold and the Interior disease from that of Liver-Heat, eventually progressing to damage of the expirational and dispersive energy of the Lung Sector, the Prime Core Organ or the excessively small organ of the Taeeum constitutional type. The resulting pathology can be broadly defined as the "Lung-Dryness symptomatology". 2) The case reports introduced in the Exterior disease section, including the Zhang Zhongjing Mahuang-tang treatment, Prolonged-affliction disease treatment, and Exterior disease Pestilential disease treatment, share several points in common. They all arise from the pathology of "weakness in the Lung sector and deficiency in the Exterior sector", and they can all be assigned to the same symptomatological division that presents with systemic heat and cold intolerance; this symptomatology can be defined as the "Esophagus-Cold symptomatology", the milder subdivision of the exterior symptomatology. 3) The body of text appearing in the last part of the Interior disease section commonly referred to as the "Taeeumin Conspectus" is in fact not a conspectus when its contents are actually examined. Instead, it can be understood from its pathological and symptomatological descriptions that the passage is explaining the more severe subdivision of the exterior symptomatology that has progressed from Esophagus-Cold to a pathology characterized by damaged expirational and dipersive energy of the Lung Sector. 4) The relocation of the "dry-related pathology" indicates a change in perspective regarding the "Dry-related symptomatology", which caused the rearrangement of the Interior disease into divisions of Liver-Heat symptomatology that is characterized by fulminant heat pathology and Dry-Heat symptomatology that is also accompanied by Lung-Dryness. 5) The Interior disease Yin-Blood Consumptive symptomatology should be included in the Dry-Heat symptomatology in the pathological scheme. 6) Based on the above, the subdivisions of the Taeeumin symptomatology should be arranged as "Esophagus-Cold symptomatology" and "Lung-Dry-Cold symptomatology" in the Exterior disease and "Liver-Heat symptomatology" and "Dry-Heat symptomatology" in the Interior disease.

• 스마트미디어저널
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• 제2권2호
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• pp.33-38
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• 2013

본 논문에서는 급성 알코올성 간 손상과 만성 에탄올성 간섬유증이 유도된 마우스로부터 획득한 라만 스펙트럼에서 배경 잡음을 제거하기 위한 기준선 추정 방법을 조사하였다. 기준선을 추정하기 위해 일차 미분, 선형계획법, rolling ball을 이용한 방법을 적용하였다. 각 방법의 적절한 압력 파라미터를 MAP(maximum a posteriori probability)의 훈련율에 의해 결정하였다. 실험 절과에 따르면 rolling ball 알고리즘을 이용한 기준선 추정 방법이 급성 알코올성 간 손상과 만성 에탄올성 간섬유증의 MAP 분류에서 평균 89.4%로 가장 좋은 결과를 나타냈다. 이 결과로부터 라만 스펙트럼의 기준선 추정에 적절한 방법과 파라미터를 결정하는 것이 분류 성능에 미치는 영향을 확인하였다.