• 한국컴퓨터정보학회논문지
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• 제26권2호
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• pp.39-44
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• 2021

본 논문에서는 가정에서 많이 기르는 반려견을 바탕으로 반려견 질병에 대한 전문적인 수의학 지식이 부족한 일반인들을 대상으로 자신의 반련견의 건강 상태를 파악할 수 있는 진단 시스템을 제안한다. 제안된 진단 시스템은 50가지 질병과 각 질병의 증상을 데이터베이스에 구축하여 입력된 증상을 통해서 반려견의 질병을 도출한다. 각 질병 데이터베이스에는 질병에 해당하는 증상 코드들을 가지고 있으며, 이러한 질병에 대한 데이터베이스를 이용하여 군집화 기법인 FCM 클러스터링 기법을 적용하여 질병을 클러스터링하고 그 결과 값인 소속도를 바탕으로 입력된 증상과 가까운 질병들을 도출하여 반려견의 진단 결과를 제공한다. 제안된 반려견 진단의 구현 결과에서는 선택한 증상들의 개수와 선택된 증상들이 포함된 질병들의 가능성 값을 구하여 내림차순으로 정렬하여 반려견의 증상과 가장 가까운 질병 상위 3가지를 도출하였다.

• 대한한의학방제학회지
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• 제25권1호
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• pp.39-49
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• 2017

Objectives : The contents of the literature associated with the medical records were entered into the database. We want to find the structure and search methods for efficient utilization of the database. Methods : The contents were entered into the database using the 'Access 2014 of the MS'. The Query Sentences were created and utilized for a search. Results : We could find information about the prescriptions, medical records and patients by the herbs and symptom combinations using the single table named 'Integrated Knowledge' and queries. Integrated Knowledge is a table that gathered patient information, prescription information and symptom information together. Conclusions : If you store patient, prescription and symptom information on a single table, you could search and use the results by various combinations of the various elements included in the table. These results could help curing patients on the basis of evidence-based treatment at the clinics.

• Safety and Health at Work
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• 제11권3호
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• pp.361-366
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• 2020

Background: This study aimed to identify the validity of breast cancer symptom questionnaire of worker's special health examination and its relationship with breast ultrasonography findings in young female night workers. Methods: The breast cancer symptom questionnaire data of worker's special health examination and breast ultrasonography results in young female shift workers who worked in one electronic manufacture company were collected from 2014 to 2018. Results: Of the 857 workers, 18 had a Breast Imaging Reporting and Database System category 4 or higher. Among other variables, shift work tenure alone was associated with the risk of having a Breast Imaging Reporting and Database System category higher than 4. The sensitivity, specificity, positive predictive value, and negative predictive value of the symptom questionnaire were 16.7%, 87.7%, 2.8%, and 98.0%, respectively. Conclusion: The current breast cancer symptom questionnaire of the worker's special health examination is inappropriate due to its low sensitivity and positive predictive value. In the future, female night workers will need alternative measures for more accurate screening for breast cancer.

• Journal of applied mathematics & informatics
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• 제32권5_6호
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• pp.737-746
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• 2014

Treatment method refers to a principle or method for treating diseases in Traditional Korean Medicine(TKM). As doctors determine the ideal treatment for a patient's disease or symptom, they are also able to prescribe effective treatment means for the diseases or symptom such as medicinal materials, prescription, acupuncture and moxibustion. Therefore, if significant symptom-treatment method combinations are found from literature or database, proper treatment means for the patient's diseases or symptom may be presented to TKM doctors and enhanced treatment accuracy and efficiency can be expected. This study aims to analyze the relation between symptom and treatment method by interpreting hypotheses through null hypotheses to find significant symptom-treatment method combinations. This combinations suggested in this study will be compared with TKM experts analysis result to find an objective analysis method and eventually apply the method to medical big data, e.g., a huge amount of literature or treatment records.

• 대한한의진단학회지
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• 제16권2호
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• pp.33-46
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• 2012

Purpose : Nowadays excrement-related disease that repeats constipation and diarrhea is on the increase due to the change of dietary and lack of exercise, etc. We analyzed Bangyakhappyeon in order to find out the materia medica which is used for the excrement patterns. Methods : The database used in present thesisis consist of disease pattern, nature of medicinals and materia medica from Bangyakhappyeon was constructed. We analyzed the nature of medicinals of excrement patterns(or symptom) by frequency analysis and network analysis, and also searched main materia medica of excrement patterns(or symptom) by frequency analysis and rule mining. Results : We analyzed the nature of medicinals of excrement patterns(or symptom) in Bangyakhappyeon. And we researched the high frequency materia medica, high specificity materia medica and high frequent paired-drugs as main materia medica of excrement patterns(or symptom). Conclusion : This study found the information about frequency relationship between excrement patterns(or symptoms) and materia medica.

• Journal of information and communication convergence engineering
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• 제19권1호
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• pp.29-35
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• 2021

While the population of pet dogs and pet-related markets are increasing, there is no convenient and reliable tool for pet health monitoring for pet owners/caregivers. In this paper, we propose a mobile platform-based pre-diagnosis system that pet owners can use for pre-diagnosis and obtaining information on coping strategies based on their observations of the pet dog's abnormal behavior. The proposed system constructs symptom-disease association databases for 100 frequently observed diseases under veterinarian guidance. Then, we apply the possibilistic fuzzy C-means algorithm to form the "probable disease" set and the "doubtable disease" set from the database. In the experiment, we found that the proposed system found almost all diseases correctly, with an average of 4.5 input symptoms and outputs 1.5 probable and one doubtable disease on average. The utility of this system is to alert the owner's attention to the pet dog's abnormal behavior and obtain an appropriate coping strategy before consult a veterinarian.

• 디지털콘텐츠학회 논문지
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• 제10권2호
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• pp.327-332
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• 2009

본 논문에서는 애견 질병에 대한 전문적인 지식이 부족한 일반인들을 대상으로 자신의 애견 건강 상태를 파악할 수 있는 진단 시스템을 제안한다. 제안된 진단 시스템은 105가지 질병과 각 질병의 증상을 데이터베이스에 구축하여 입력된 증상을 통해서 애견의 질병을 도출한다. 신경망의 자율 학습 방법인 ART2 알고리즘을 적용하여 질병을 클러스터링하고 그 결과 값인 클러스터의 출력값과 연결강도를 데이터베이스에 저장한 후 질병의 증상과 관련된 질의 결과를 입력 벡터로 제시하여 학습된 질병 정보와 비교하여 애견의 건강 상태를 진단한다. 애견의 건강 상태를 진단하는데 있어서 질병과 증상의 정확한 정보는 매우 중요하다. 따라서 본 논문에서는 질병과 증상의 정보를 데이터베이스로 구축하고 질병과 증상 정보를 효율적으로 관리할 수 있도록 하였다. 제안된 진단 시스템을 구현하여 수의학 전문의가 분석한 결과, 본 논문에서 제안한 시스템이 애견 질병의 보조 진단 시스템으로서의 가능성을 확인하였다.

• 대한예방한의학회지
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• 제17권3호
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• pp.129-141
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• 2013

Objectives : Anorexia is the primary symptom impinging cancer patients' Quality of Life. It is usually accompanied by gastrointestinal symptoms(GI symptoms). Thus, to measure anorexia symptom precisely, assessing anorexia and GI symptoms together is recommended. This study was designed to analyze cancer-related anorexia assessment tools, extract GI symptoms included in these tools and investigate usefulness of instruments in clinical trials. Methods : Instruments were selected by searching PubMed, PROQOLID database. We analyzed instruments by number of items, assessment method, type of question, GI symptoms. Results : 9 instruments were selected to assess cancer-related anorexia symptom. Most tools adopt Likert scale as response scale and 'during past week' as recall period. Assessment method of all 9 instruments is the self-administration. Questions measuring anorexia are able to be sorted into 3 forms (frequency, severeness, distress of anorexia symptom). Among the GI symptoms, nausea is included in all 9 instruments. In clinical trials of cancer-related anorexia, Edmonton Symptom Assessment Scale(ESAS) and Functional Assessment of Anorexia/Cachexia Therapy Questionnaire(FAACT) were selected as endpoint measure. Conclusions : The result showed that FAACT is the only specialized tool to assess cancer-related anorexia. To measure cancer-related anorexia precisely, the need to develop new instrument exists.

• 대한한의학회지
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• 제41권3호
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• pp.1-8
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• 2020

Objectives: This paper aims to investigate the Donguibogam-based pattern diagnosis by applying natural language processing and machine learning. Methods: A database has been constructed by gathering symptoms and pattern diagnosis from Donguibogam. The symptom sentences were tokenized with nouns, verbs, and adjectives with natural language processing tool. To apply symptom sentences into machine learning, Word2Vec model has been established for converting words into numeric vectors. Using the pair of symptom's vector and pattern diagnosis, a pattern prediction model has been trained through Logistic Regression. Results: The Word2Vec model's maximum performance was obtained by optimizing Word2Vec's primary parameters -the number of iterations, the vector's dimensions, and window size. The obtained pattern diagnosis regression model showed 75% (chance level 16.7%) accuracy for the prediction of Six-Qi pattern diagnosis. Conclusions: In this study, we developed pattern diagnosis prediction model based on the symptom and pattern diagnosis from Donguibogam. The prediction accuracy could be increased by the collection of data through future expansions of oriental medicine classics.

• 한국정보전자통신기술학회논문지
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• 제2권3호
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• pp.23-29
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• 2009

심박수는 심장이 혈액을 전신에 보낼 때에 고동치는 속도, 즉 매 분당 박동수를 말하 며 성인남자의 경우 보통 1분동안 60~80회가 정상적이다. 심박수가 정상보다 적으면 서맥, 많으면 빈맥이라 하며 이 경우 여러 가지 질병에 걸릴 수 있으며 상황에 따라 사망에 이르기까지도 한다. 따라서 심박수는 건강한 생활에 매우 중요한 역할을 하고 있다. 본 연구에서는 ECG를 통하여 심박수를 자동 추출하는 방법에 관하여 연구하였다. 육안으로 측정한 심박수를 기준으로 첫째 ECG를 2차 미분을 이용하여 심박수를 추출하는 방법과 자기상관함수를 이용하여 심박수를 추출한 방법으로 구한 심박수를 비교하여 고찰 하였다. 실험 데이터는 MIT/BIH Database를 이용하였다.