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박형섭 ( Hyoung Seob Park ),한성욱 ( Seongwook Han ) 대한내과학회 2016 대한내과학회지 Vol.90 No.2
Implantable cardioverter-defibrillators (ICDs) are an effective treatment strategy for patients with aborted sudden cardiac death (SCD) and ventricular tachyarrhythmias. rimary prevention of SCD is a strategy involving the use of ICDs in patients who are at high risk for, but have not had, any previous events of ventricular arrhythmias or cardiac arrest. Several randomized clinical trials have demonstrated the efficacy of ICDs in the primary prevention of SCD. Therefore, ICD implantation is recommended as a standard of care by the guidelines in patients who have ischemic or nonischemic cardiomyopathy and a low left ventricular ejection fraction. However, the rates of ICD implantation as a primary prevention in Korea is quite low compared to western countries. In this review, we will summarize the results and efficacy of ICDs in the clinical trials about primary prevention of SCD, the current treatment guidelines, and the reimbursement policy of Korean health insurance. We hope that this review will help broaden the recognition of importance of ICD implantation for the primary prevention of SCD. (Korean J Med 2016;90:115-120)
손창식(Chang-Sik Son),강원석(Won-Seok Kang),최락현(Rock-Hyun Choi),박형섭(Hyoung-Seob Park),한성욱(Seongwook Han),김윤년(Yoon-Nyun Kim) 한국산업정보학회 2015 한국산업정보학회논문지 Vol.20 No.3
본 논문에서는 이산 웨이블릿 변환을 통해 추출된 시간 영역과 주파수 영역의 특징들을 활용하여 심박수변이도를 확률적인 지식으로 분석할 수 있는 방법을 제안하였다. 제안된 방법에서 지식획득 알고리즘은 규칙생성과 규칙평가 단계로 구성되어 있으며, 규칙생성에서는 ROC 분석을 통해 수치적인 속성값을 이산화된 구간으로 변환하고, 서로 다른 의사결정값을 포함하는 구간들 사이에 일관성 정도를 비교함으로써 감축된 규칙-집합을 생성한다. 이때 규칙-집합 내에 각 규칙에 대해서 확률적 해석을 위한 3가지 척도를 추정하였다. 제안된 모형의 효과성은 심혈관질환 병력을 가진 58명의 심전도 데이터로부터 심방세동을 식별할 수 있는 5가지 규칙을 생성하였고, 이들 규칙의 분별력을 평가하였다. 실험결과, 제안된 모형으로부터 생성된 지식은 4가지 성능평가 척도에 대해서 각각 93%의 정확도를 보여주었다. This study presents a probabilistic knowledge discovery method to interpret heart rate variability (HRV) based on time and frequency domain indexes, extracted using discrete wavelet transform. The knowledge induction algorithm was composed of two phases: rule generation and rule estimation. Firstly, a rule generation converts numerical attributes to intervals using ROC curve analysis and constructs a reduced ruleset by comparing consistency degree between attribute-value pairs with different decision values. Then, we estimated three measures such as rule support, confidence, and coverage to a probabilistic interpretation for each rule. To show the effectiveness of proposed model, we evaluated the statistical discriminant power of five rules (3 for atrial fibrillation, 1 for normal sinus rhythm, and 1 for both atrial fibrillation and normal sinus rhythm) generated using a data (n=58) collected from 1 channel wireless holter electrocardiogram (ECG), i.e., HeartCall<SUP>®</SUP>, U-Heart Inc. The experimental result showed the performance of approximately 0.93 (93%) in terms of accuracy, sensitivity, specificity, and AUC measures, respectively.