• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.868-871
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• 2006

Mortality of domestic people from cardiovascular disease ranked second, which followed that of from cancer last year. Therefore, it is very important and urgent to enhance the reliability of medical examination and treatment for cardiovascular disease. Heart Rate Variability (HRV) is the most commonly used noninvasive methods to evaluate autonomic regulation of heart rate and conditions of a human heart. In this paper, our aim is to extract a quantitative measure for HRV to enhance the reliability of medical examination for cardiovascular disease, and then develop a prediction method for extracting multi-parametric features by analyzing HRV from ECG. In this study, we propose a hybrid Bayesian classifier called FP-based Bayesian. The proposed classifier use frequent patterns for building Bayesian model. Since the volume of patterns produced can be large, we offer a rule cohesion measure that allows a strong push of pruning patterns in the pattern-generating process. We conduct an experiment for the FP-based Bayesian classifier, which utilizes multiple rules and pruning, and biased confidence (or cohesion measure) and dataset consisting of 670 participants distributed into two groups, namely normal and patients with coronary artery disease.

• 한국인공지능학회지
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• 제6권2호
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• pp.17-22
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• 2018

According to the World Health Organization, the top 10 causes of death worldwide include heart disease. Heart diseases include coronary disease, which induces acute myocardial infarction. Ticagrelor drugs are being used to treat acute alliances, but it has become difficult to breathe due to the drugs. In a related study, Tobias predicted that uric acid causes acute respiratory distress independently of other factors, including BNP. And in the Ahmad study, serum uric acid numbers were related to the left ventricle depending on the level of uric acid. Experimental data are data used after 155 patients who received coronary intervention took ticagrelor. The research methods were leveraged by gradient decent algorithm and linear regression. In order to avoid overfitting in the experiment, training data and test data were separated into 70 and 30 percent respectively. The experimental results lacked the predictability of other attributes except DT in the correlation coefficient and crystal coefficient. However, all attributes related to dyspnea other than DT are determined to be related to causing relaxation of the heart in the left ventricle. Therefore, the attribute causing dyspnea is determined to be an attribute causing relaxation of the heart of the DT and left ventricle.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2022년도 추계학술발표대회
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• pp.55-56
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• 2022

Hypertension is a severe health problem and increases the risk of other health issues, such as heart disease, heart attack, and stroke. In this research, we propose a machine learning-based prediction method for the risk of chronic hypertension. The proposed method consists of four main modules. In the first module, the linear interpolation method fills missing values of the integration of gas and meteorological datasets. In the second module, the OrdinalEncoder-based normalization is followed by the Decision tree algorithm to select important features. The prediction analysis module builds three models based on k-Nearest Neighbors, Decision Tree, and Random Forest to predict hypertension levels. Finally, the features used in the prediction model are explained by the DeepSHAP approach. The proposed method is evaluated by integrating the Korean meteorological agency dataset, natural gas leakage dataset, and Korean National Health and Nutrition Examination Survey dataset. The experimental results showed important global features for the hypertension of the entire population and local components for particular patients. Based on the local explanation results for a randomly selected 65-year-old male, the effect of hypertension increased from 0.694 to 1.249 when age increased by 0.37 and gas loss increased by 0.17. Therefore, it is concluded that gas loss is the cause of high blood pressure.

• 한국컴퓨터정보학회논문지
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• 제27권5호
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• pp.21-28
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• 2022

심혈관질환은 심장질환과 혈관질환 등 순환기계통에 생기는 모든 질병을 통칭한다. 심혈관질환은 2019년 사망의 1/3을 차지하는 전 세계 사망의 주요 원인이며, 사망자는 계속 증가하고 있다. 이와 같은 질병을 인공지능을 활용해 환자의 데이터로 미리 예측이 가능하다면 질병을 조기에 발견해 치료할 수 있을 것이다. 본 연구에서는 심혈관질환 중 하나인 심장질환을 예측하는 모델들을 생성하였으며 Accuracy, Precision, Recall의 측정값을 지표로 하여 모델들의 성능을 비교한다. 또한 Decision Tree의 성능을 향상시키는 방법에 대해 기술한다. 본 연구에서는 macOS Big Sur환경에서 Jupyter Notebook으로 Python을 사용해 scikit-learn, Keras, TensorFlow 라이브러리를 이용하여 실험을 진행하였다. 연구에 사용된 모델은 Decision Tree, KNN(K-Nearest Neighbor), SVM(Support Vector Machine), DNN(Deep Neural Network)으로 총 4가지 모델을 생성하였다. 모델들의 성능 비교 결과 Decision Tree 성능이 가장 높은 것으로 나타났다. 본 연구에서는 노드의 특성배치를 변경하고 트리의 최대 깊이를 3으로 지정한 Decision Tree를 사용하였을 때 가장 성능이 높은 것으로 나타났으므로 노드의 특성 배치 변경과 트리의 최대 깊이를 설정한 Decision Tree를 사용하는 것을 권장한다.

• 대한영상의학회지
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• 제82권5호
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• pp.1163-1185
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• 2021

급성 심장사는 증상이 시작된 후 한 시간 이내에 발생하는 심장 원인으로 인한 사망이다. 급성 심장사의 원인은 주로 부정맥이지만 동반할 수 있는 기저 심질환들을 사전에 진단하는 것은 장기적 위험을 예측하는 데 중요하다. 심장 CT와 심장 MR은 구조적 심질환을 진단하고 평가하는데 중요한 정보를 제공하여 급성 심장사의 위험을 예측하고 대비할 수 있게 한다. 따라서 임상적으로 중요한 급성 심장사의 위험을 증가시키는 다양한 원인과 영상 소견의 중요성에 대하여 중점적으로 살펴보고자 한다.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• 제30권5호
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• pp.414-421
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• 2004

This is a reprospective study on the care of odontogenic infections in admission patients with geriatric diseases. The study was based on a series of 480 patients at Dong San Medical Center, Wonju Christian Hospital and Il San Health Insurance Hospital, From Jan. 1, 2000, to Dec. 31, 2002. The Obtained results were as follows: 1. The systemic malignant tumor was the most frequent cause of the geriatric diseases with odontogenic infectious diseases, and refractory lung disease, systemic heart disease, type II diabetes mellitus, cerebrovascular disease, bone & joint disease, senile psychologic disease were next in order of frequency. 2. Male prediction(57.5%) was existed in the odontogenic infectious patients with geriatric diseases. But, there were female prediction in senile psychologic disease, systemic heart disease and cerebrovascular disease. 3. The most common age group of the odontogenic infectious patient with geriatric disease was the sixty decade(47.9%), followed by the seventy & eighty decade in order. 4. In the contents of chief complaints on the odontogenic infectious patients with geriatric disease, peak incidence was occurred as toothache(52.7%), followed by extraction wish, tooth mobility, oral bleeding, oral ulcer, fracture of restoration, gingival swelling in order. 5. In the diagnosis group of odontogenic infectious diseases, periodontitis, pulpitis & periapical abscess were more common. 6. In the treatment group of odontogenic infectious diseases, the most frequent incidence(34.2%) was showed in primary endodontic treatment (pulp extirpation, occlusal reduction and canal opening drainage) and followed by scaling, incision & drainage, only drugs, pulp capping, restoration in order.

• 지질동맥경화학회지
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• 제7권2호
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• pp.110-121
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• 2018

Objective: We developed a new equation for predicting coronary heart disease (CHD) risk in Korean diabetic patients using a hospital-based cohort and compared it with a UK Prospective Diabetes Study (UKPDS) risk engine. Methods: By considering patients with type 2 diabetes aged ${\geq}30years$ visiting the diabetic center in Boramae hospital in 2006, we developed a multivariable equation for predicting CHD events using the Cox proportional hazard model. Those with CHD were excluded. The predictability of CHD events over 6 years was evaluated using area under the receiver operating characteristic (AUROC) curves, which were compared using the DeLong test. Results: A total of 732 participants (304 males and 428 females; mean age, $60{\pm}10years$; mean duration of diabetes, $10{\pm}7years$) were followed up for 76 months (range, 1-99 month). During the study period, 48 patients (6.6%) experienced CHD events. The AUROC of the proposed equation for predicting 6-year CHD events was 0.721 (95% confidence interval [CI], 0.641-0.800), which is significantly larger than that of the UKPDS risk engine (0.578; 95% CI, 0.482-0.675; p from DeLong test=0.001). Among the subjects with <5% of risk based on the proposed equation, 30.6% (121 out of 396) were classified as ${\geq}10%$ of risk based on the UKPDS risk engine, and their event rate was only 3.3% over 6 years. Conclusion: The UKPDS risk engine overestimated CHD risk in type 2 diabetic patients in this cohort, and the proposed equation has superior predictability for CHD risk compared to the UKPDS risk engine.

• Journal of Cardiovascular Imaging
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• 제31권1호
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• pp.1-17
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• 2023

The Coronary Artery Calcium Data and Reporting System (CAC-DRS) is a standardized reporting method for calcium scoring on computed tomography. CAC-DRS is applied on a per-patient basis and represents the total calcium score with the number of vessels involved. There are 4 risk categories ranging from CAC-DRS 0 to CAC-DRS 3. CAC-DRS also provides risk prediction and treatment recommendations for each category. The main strengths of CAC-DRS include a detailed and meaningful representation of CAC, improved communication between physicians, risk stratification, appropriate treatment recommendations, and uniform data collection, which provides a framework for education and research. The major limitations of CAC-DRS include a few missing components, an overly simple visual approach without any standard reference, and treatment recommendations lacking a basis in clinical trials. This consistent yet straightforward method has the potential to systemize CAC scoring in both gated and non-gated scans.

• 한국산학기술학회논문지
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• 제20권8호
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• pp.331-343
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• 2019

본 연구는 Framingham Heart Study의 심장나이 예측 모형을 활용하여 심장나이의 추이를 관찰하여 한국인 심혈관질환 발생 위험을 평가해보고자 하였다. 연구대상은 2005년~2013년 국민건강영양조사 자료를 이용하여 30세~74세 대상자 중 심혈관질환 기왕력이 없고, 모형의 결정요인에 해당하는 자료의 결손이 없는 20,012명을 연구대상으로 하였다. 이들에 대해 Framingham Heart Study 비실험실 자료를 이용하는 심장나이 산정 모형을 적용하여 심장나이를 계산하였으며 성별로 심장나이와 실제나이와의 차이, 연령대별 차이, 10년 이상 초과율, 지역별 차이에 대해 연도별 추이를 관찰하였다. 자료분석은 SAS 9.3으로 수행하였으며 가중치를 적용한 복합표본설계분석을 수행하였다. 연구 결과 심장나이와 실제나이의 평균 차이는 남성은 2005년에 7.8세, 2013년 7.7세, 여성은 2005년 1.2세 2013년 1.2세로 남성이 여성보다 컸고, 연령대가 증가할수록 나이차이가 많아졌으며, 연도별로 뚜렷한 추이 변화는 없었다. 심장나이가 실제 나이보다 10년 이상 초과한 비율은 남성은 2005년에 35.0%, 2013년에 34.8%, 여성은 2005년에 17.7%, 2013년에 18.7%로 남성이 여성보다 거의 두 배 정도 높았으며 연령대가 증가할수록 차이가 많이 났다. 지역별로 차이를 보였으며 남녀 차이가 많았다. 본 연구결과로 볼 때 한국인의 10년 내 심혈관질환 발생 가능성은 상당히 높은 수준이었다. 본 연구에서 사용한 심장나이는 미래의 심혈관질환 발병 위험을 간단하고 편리하게 예측할 수 있는 유용한 종합 지표로 사용될 수 있으며, 이를 한국인 심혈관질환 예방을 위한 경고효과와 계도목적으로 현장에서 공중보건 관리에 활용되기를 제안한다. 한국형 심장나이 예측 모형의 개발을 위한 심층 연구도 필요하다.

• International Journal of Computer Science & Network Security
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• 제24권3호
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• pp.43-52
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• 2024

Health Monitoring System is a sophisticating technology and another way to the normal/regular management of the health of the patient. This Health Monitoring Mobile Application is a contribution from our side to the public and to the overall health industry in Pakistan. With the help of Health mobile application, the users will be able to store their medical records, prescriptions and retrieve them later. The users can store and keep track of their vital readings (heart rate, blood pressure, fasting glucose, random glucose). The mobile application also shows hospitals that are nearby in case the user wants to avail of any medical help. An important feature of the application is the symptoms-based disease prediction, the user selects the symptoms which he has and then the application will name certain diseases that match those symptoms based on relevant algorithms. The major advances and issues have been discussed, and as well as potential tasks to health monitoring will be identified and evaluated.