• 제목/요약/키워드: Diagnosis classification

검색결과 1,247건 처리시간 0.028초

질감 기반 이미지 검색을 위한 질감 서술자 및 컴퓨터 조력 진단 시스템의 적용 (Texture Descriptor for Texture-Based Image Retrieval and Its Application in Computer-Aided Diagnosis System)

  • 뮤잠멜;팽소호;김덕환
    • 전자공학회논문지CI
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    • 제47권4호
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    • pp.34-43
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    • 2010
  • 질감 정보는 객체 인식과 분류에서 중요한 역할을 하고 있다. 정확한 질환 판별을 위해 분류에서 사용되는 질감 특징은 식별성이 높아야 한다. 본 논문에서는 질감-기반 영상 검색 및 폐기종 진단을 위해 컴퓨터 조력진단(Computer-Aided Diagnosis) 시스템을 위한 새로운 질감 기술자를 제안한다. 제안한 질감 기술자는 이웃화소간의 차이값과 중심화소와 이웃화소간의 차이 값의 결합에 기반을 두고 있어 결합된 주변화소 차이(Combined Neighborhood Difference; CND)라고 한다. 화소들간의 CND는 비교후 이진 코드워드로 변환된다. 그다음에, 식별성이 높은 값을 생성하기 위하여 이진 계수가 코드워드에 할당된다. 이와 같은 값들의 분포가 계산되어 질감 특징 벡터를 구성한다. Outex와 Brodatz 데이터집합을 이용한 질감 특징 분류에 관련하여 CND는 92.5%의 정확성을 보이는 데 비해, LBP, LND와 Gabor 픽터는 89.3%, 90.7%와 83.6%의 정확성을 각각 보여준다. 본 논문에서는 CND를 이용한 폐기종의 진단 기능을 CAD 시스템에서 구현하였다.

한국 표준 간호행위 분류 (The Classification of Standard Nursing Activities in Korea)

  • 박정호;성영희;송미숙;조정숙;심원희
    • 대한간호학회지
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    • 제30권6호
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    • pp.1411-1426
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    • 2000
  • A nursing activity classification for hospitalized patients was performed based on an article review regarding nursing definition and nursing activity classification system. The study was conducted as follows: 1) Taxonomy was developed by the research team through the Delphi process and review article. The taxonomy consists of four nursing processes, (assessment, diagnosis, intervention and evaluation) and twelve nursing activity domains space (resperation, nutrition, elimination, exercise/alignment maintenance, comfort, hygiene, safety, spiritual support, counseling/ education, medication, communication, patient and information management). 2) First, nursing activities of the intervention process were listed and then classified by the nursing process of assessment, diagnosis, intervention and evaluation. The list consists of twelve nursing activity domains and 136 nursing activities. 3) A pilot study was conducted in two hospitals to verify validity and appropriateness of nursing activities. 4) The content validity index, which was calculated by 6 clinical practice experts, was 0.95. Also, a nursing activity classification system should also be developed in the department of community nursing and home health care nursing.

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퍼지 패턴 분류와 뉴럴 네트워크를 이용한 지능형 유중가스 판정 시스템 (Intelligent Diagnosis System for DGA Using Fuzzy Pattern Classification and Neural Network)

  • 조성민;권동진;남창현;김재철
    • 전기학회논문지
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    • 제56권12호
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    • pp.2084-2090
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    • 2007
  • The DGA (Dissolved Gases Analysis) technique has been widely using for fault diagnosis of the power transformers. Some electric power utility company establishes the criteria of DGA to improve reliability, because of difference of operation environment and design of power transformer. In this paper, we introduce intelligent diagnosis system for DGA result of KEPCO (Korea Electric Power Cooperation). This system can classify patterns type of gases ratio that frequently occurs in recent result of gases analysis using Fuzzy Inference. The classification of Patterns let us know that major causes of gases generation based on type of patterns. Finally, Neural Network based on patterns diagnose transformer. NN was trained using result data of DGA of actually faulted transformers recently. Result of intelligent diagnosis system is right well in comparison with actual inner inspection of transformers.

의사결정나무법을 이용한 체질진단에 관한 연구 (A study of constitution diagnosis using decision tree method)

  • 이영섭;박성식;박은경
    • 사상체질의학회지
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    • 제13권2호
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    • pp.144-155
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    • 2001
  • By the increasing concern about Sasang Constitution Medicine, its practical use is considered very important in disease prevention and medical treatment. However, the method of constitution classification is depending on the doctor's clinical trials because of the lack of the objective test criteria. This study is trying to improve the objectiveness of diagnosis using a new statistical method, decision tree. Decision tree method-a classification technique in the statistical analysis- was used to analyze the result of QSCCII instead of using discriminant analysis. As a result, 16 among 121 QSCCII questions was selected as important questions and 21 terminal nodes was built to classify the constitution. Using only 16 questions shown in the result of decision tree, we can diagnose and interpret the constitution easily and effectively.

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Alternative accuracy for multiple ROC analysis

  • Hong, Chong Sun;Wu, Zhi Qiang
    • Journal of the Korean Data and Information Science Society
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    • 제25권6호
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    • pp.1521-1530
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    • 2014
  • The ROC analysis is considered for multiple class diagnosis. There exist many criteria to find optimal thresholds and measure the accuracy of diagnostic tests for k dimensional ROC analysis. In this paper, we proposed a diagnostic accuracy measure called the correct classification simple rate, which is defined as the summation of true rates for each classification distribution and expressed as a function of summation of sequential true rates for two consecutive distributions. This measure does not weight accuracy across categories by the category prevalence and is comparable across populations for multiple class diagnosis. It is found that this accuracy measure does not only have a relationship with Kolmogorov - Smirnov statistics, but also can be represented as a linear function of some optimal threshold criteria. With these facts, the suggested measure could be applied to test for comparing multiple distributions.

조기 위암의 진단에 있어서 확대 내시경을 동반한 협대역 내시경의 역할 (Clinical Role of Magnifying Endoscopy with Narrow-band Imaging in the Diagnosis of Early Gastric Cancer)

  • 최수인
    • Journal of Digestive Cancer Research
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    • 제10권2호
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    • pp.56-64
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    • 2022
  • Narrow-band imaging (NBI) is the most widely used image-enhanced endoscopic technique. The superficial microanatomy of gastric mucosa can be visualized when used with a magnifying endoscopy with narrow-band imaging (ME-NBI). The diagnostic criteria for early gastric cancer (EGC), using the classification system for microvascular and microsurface pattern of ME-NBI, have been developed, and their usefulness has been proven in the differential diagnosis of small depressed cancer from focal gastritis and in lateral extent delineation of EGC. Some studies reported on the prediction of histologic differentiation and invasion depth of gastric cancer using ME-NBI; however, its application is limited in clinical practice, and further well-designed studies are necessary. Clinicians should understand the ME-NBI classification system and acquire appropriate diagnostic skills through various experiences and training to improve the quality of endoscopy for EGC diagnosis.

고전에 나타난 요통 및 관련 전신 증상에 관한 문헌적 고찰 - 한의학적 분류 및 진단 체계의 표준화를 위한 기초 자료 수집을 중심으로 - (A Bibliographic Study on Low Back Pain and Related General Symptoms in Classical Literatures - Standardization for Classification and Diagnosis of Low Back Pain -)

  • 곽현영;남동우;강중원;김은정;김갑성;최도영;이재동
    • Journal of Acupuncture Research
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    • 제27권1호
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    • pp.31-41
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    • 2010
  • Objectives : The purpose of this study is to set up the standard for Classification and Diagnosis of Low Back Pain by through collecting bibliographic study on Low Back Pain and related general symptoms in classical literatures Methods : We investigated the contents of classical literatures about chronic low back pain and related general symptoms. With this contents, we established a systemic classification and diagnostic standard for Low back pain. Results : There are many different opinions on classification of low back pain and general symptoms in oriental medicine classical literature. Every opinion is reasonable, so it is difficult to establish a diagnosis of Low back pain. But it is necessary to set up the one-systemic classification and diagnostic technique of Low back pain. Conclusions : We conclude that the Ten type Low back pain classification of in Dong-Eui-Bo-Gam is a reasonable standard for diagnostic classification.

산부인과 간호단위의 간호과정과 SNOMED CT를 이용한 간호진단 온톨로지의 구축 (Construction of the Nursing Diagnosis Ontology in Obstetric and Gynecologic Nursing Unit using Nursing Process and SNOMED CT)

  • 박정은;정귀애;조훈;김화선
    • 여성건강간호학회지
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    • 제19권1호
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    • pp.1-12
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    • 2013
  • Purpose: This study was performed to propose an ontology methodology based on standardized nursing process as framework in obstetric and gynecologic nursing practice. Methods: The instrument used in this study was based on the nursing diagnosis classification established by North American Nursing Diagnosis Association (NANDA) (2009-2011), fifth edition of the Nursing Interventions Classification (NIC) (2008), forth edition of the Nursing Outcomes Classification (NOC) (2008) developed by Iowa State University and systematized nomenclature of medicine clinical terms (SNOMED CT). The nursing records data were collected from electronic medical records of one hospital from August to October 2010. Results: One hundred and forty-one nursing diagnosis statements used in obstetric and gynecologic nursing unit were linked standardized nursing classifications and constructed nursing diagnosis ontology including interoperability. Conclusion: Not only will this result be helpful to complete nurse's lack of knowledge and experience, it will also help to determine nursing diagnosis logically by using standardized nursing process. It will be utilized as the method to construct ontology including interoperability in other nursing units. It will be presented nursing interventions according to nursing diagnosis and thus will be easier to establish nursing planning. This can provide immediate feedback of the nursing process application.

CIM 구축을 위한 지능형 고장진단 시스템 개발 (Development of Intelligent Fault Diagnosis System for CIM)

  • 배용환;오상엽
    • 한국산업융합학회 논문집
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    • 제7권2호
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    • pp.199-205
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    • 2004
  • This paper describes the fault diagnosis method to order to construct CIM in complex system with hierarchical structure similar to human body structure. Complex system is divided into unit, item and component. For diagnosing this hierarchical complex system, it is necessary to implement a special neural network. Fault diagnosis system can forecast faults in a system and decide from the signal information of current machine state. Comparing with other diagnosis system for a single fault, the developed system deals with multiple fault diagnosis, comprising hierarchical neural network (HNN). HNN consists of four level neural network, i.e. first is fault symptom classification and second fault diagnosis for item, third is symptom classification and forth fault diagnosis for component. UNIX IPC is used for implementing HNN with multitasking and message transfer between processes in SUN workstation with X-Windows (Motif). We tested HNN at four units, seven items per unit, seven components per item in a complex system. Each one neural network represents a separate process in UNIX operating system, information exchanging and cooperating between each neural network was done by message queue.

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계층구조 접근에 의한 복합시스템 고장진단 기법 (Fault Diagnosis Method of Complex System by Hierarchical Structure Approach)

  • 배용환;이석희
    • 한국정밀공학회지
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    • 제14권11호
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    • pp.135-146
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    • 1997
  • This paper describes fault diagnosis method in complex system with hierachical structure similar to human body structure. Complex system is divided into unit, item and component. For diagnosing this hierarchical complex system, it is necessary to implement special neural network. Fault diagnosis system can forecast faults in a system and decide from current machine state signal information. Comparing with other diagnosis system for single fault, the developed system deals with multiple fault diagnosis comprising Hierarchical Neural Network(HNN). HNN consists of four level neural network, first level for item fault symptom classification, second level for item fault diagnosis, third level for component symptom classification, forth level for component fault diagnosis. UNIX IPC(Inter Process Communication) is used for implementing HNN wiht multitasking and message transfer between processes in SUN workstation with X-Windows(Motif). We tested HNN at four units, seven items per unit, seven components per item in a complex system. Each one neural newtork operate as a separate process in HNN. The message queue take charge of information exdhange and cooperation between each neural network.

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