• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.252-255
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• 2016

The objective of this paper is to find an easier and non-invasive a way of diagnosing heart diseases based on the heart sound, rigidly heart murmurs, recordings from subjects. Although most of the heart sounds can be easily heard, analysis of the findings by auscultation strongly depends on skills and experience of the physician. Therefore, the heart murmur is require quantitative analysis for automatic diagnosis equipment. For a good sound analysis, the noisy component ware filtered. This can be done using Wiener filter. Once the signal is filtered, it can be segmented into its basic components by signal energy using FFT. After segment the heart sound signal, the relative positions of the different heart sound components will be identified and will be used for quantification purposes. We are using murmur energy ratio. The experimental results are fairly good in relation to automatic diagnosis.

• Journal of information and communication convergence engineering
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• v.20 no.1
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• pp.31-40
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• 2022

Coronary heart disease (CHD) is a comorbidity of COVID-19; therefore, routine early diagnosis is crucial. A large number of examination attributes in the context of diagnosing CHD is a distinct obstacle during the pandemic when the number of health service users is significant. The development of a precise machine learning model for diagnosis with a minimum number of examination attributes can allow examinations and healthcare actions to be undertaken quickly. This study proposes a CHD diagnosis model based on feature selection, data balancing, and ensemble-based classification methods. In the feature selection stage, a hybrid SVM-GA combined with fast correlation-based filter (FCBF) is used. The proposed system achieved an accuracy of 94.60% and area under the curve (AUC) of 97.5% when tested on the z-Alizadeh Sani dataset and used only 8 of 54 inspection attributes. In terms of performance, the proposed model can be placed in the very good category.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.8B
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• pp.830-838
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• 2009

Oriental medicine lacks diagnosis data in fixed quantity possible to express visually to patients by depending on clinician's intuition than Western medicine that continues to development by various diagnosis devices. For that, this paper intends to examine relation between heart and voice signal regarded as center organ and source of life and mind in order to implement objectification through the visualization of oriental diagnosis method above all. According to because the heart is related to the tongue among five organs, by thinking with sounds, we would design the way of identifying existence of heart diseases focused on the fact that lingual sound pronunciation of heart patient is inexact. For this, we achieved a comparison, analysis of statistical bandwidth and morphological modeling of the second formants frequency about a lingual sound for their voice constituted subject group of heart diseases and normal people. Finally, we analyzed interrelationship to the result of experiment by designed method.

• Korean Circulation Journal
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• v.53 no.4
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• pp.195-216
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• 2023

The Korean Society of Heart Failure guidelines aim to provide physicians with evidence-based recommendations for diagnosing and managing patients with heart failure (HF). In Korea, the prevalence of HF has been rapidly increasing in the last 10 years. HF has recently been classified into HF with reduced ejection fraction (EF), HF with mildly reduced EF, and HF with preserved EF (HFpEF). Moreover, the availability of newer therapeutic agents has led to an increased emphasis on the appropriate diagnosis of HFpEF. Accordingly, this part of the guidelines will mainly cover the definition, epidemiology, and diagnosis of HF.

• The Journal of the Acoustical Society of Korea
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• v.25 no.3
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• pp.144-150
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• 2006

Clinicians usually use stethoscopic auscultation for the diagnosis of heart diseases. However, the heart sound signal has varying characteristics due to the noise and/or the conditions of the patients. Also, it is not easy for junior clinicians to find the acoustical differences between different kinds or heart sound signals. which may result in errors in the diagnosis. Thus it will be quite useful for the clinicians to make use of an automatic classification system using signal processing techniques. In this paper, we propose to use hidden Markov models in stead of artificial neural networks which have been conventionally used for the automatic classification of heart sounds. In the experiments classifying heart sound signals. we could see that the proposed methods were quite successful in the classification accuracy.

• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1031-1040
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• 2004

Electrocardiogram being the recording of the heart's electrical activity provides valuable clinical information about heart's status. Many re-searches have been pursued for heart disease diagnosis using ECG so far. However, electrocardio-graph uses foreign diagnosis algorithm due to inaccuracy of diagnosis results for a heart disease. This paper suggests ECG data collection, data preprocessing and heart disease pattern classification using data mining. This classification technique is the FB(Frequent pattern Bayesian) classifier and is a combination of two data mining problems, naive bayesian and frequent pattern mining. FB uses Product Approximation construction that uses the discovered frequent patterns. Therefore, this method overcomes weakness of naive bayesian which makes the assumption of class conditional independence.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.503-512
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• 2007

An infant of a baby child who haven't communication skills through a language expresses their intention or baby condition as generally crying. Among these things, it is important to show a baby condition because their disease miss diagnosis time or remain to decide an exact diagnosis result too hard. For this, in this paper, we are going to develop system which decides where to be not good body point by analysing their face color and crying sound. Specifically, in this paper, we are going to act for baby heart diseases by doing feature extraction for their face region color and crying sound. To embody, we are going to present diagnosis method and compare analyze their crying sound a stand child, a different diseases child and a baby heart diseases child through each analyzed element. And also, we are going to extract matters to be attended to baby heart diseases through experiment and prepare objective index and an accuracy of baby heart diseases diagnosis result.

• Clinical and Experimental Pediatrics
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• v.54 no.5
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• pp.183-191
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• 2011

Although antenatal diagnostic technique has considerably improved, precise detection and proper management of the neonate with congenital heart disease (CHD) is always a great concern to pediatricians. Congenital cardiac malformations vary from benign to serious conditions such as complete transposition of the great arteries (TGA), critical pulmonary and aortic valvular stenosis/atresia, hypoplastic left heart syndrome (HLHS), obstructed total anomalous pulmonary venous return (TAPVR), which the baby needs immediate diagnosis and management for survival. Unfortunately, these life threatening heart diseases may not have obvious evidence early after birth, most of the clinical and physical findings are nonspecific and vague, which makes the diagnosis difficult. High index of suspicion and astute acumen are essential to decision making. When patent ductus arteriosus (PDA) is opened Widely, many serious malformations may not be noticed easily in the early life, but would progress as severe acidosis/shock/cyanosis or even death as PDA constricts after few hours to days. Ductus dependent congenital cardiac lesions can be divided into the ductus dependent systemic or pulmonary disease, but physiologically quite different from each other and treatment strategy has to be tailored to the clinical status and cardiac malformations. Inevitably early presentation is often regarded as a medical emergency. Differential diagnosis with inborn error metabolic disorders, neonatal sepsis, persistent pulmonary hypertension of the newborn (PPHN) and other pulmonary conditions are necessary. Urgent identification of the newborn at such high risk requires timely referral to a pediatric cardiologist, and timely intervention is the key in reducing mortality and morbidity. This following review deals with the clinical presentations, investigative modalities and approach to management of congenital cardiac malformations presenting in the early life.

• Journal of Korean Neurosurgical Society
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• v.30 no.3
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• pp.389-394
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• 2001

Cerebral dural sinus thrombosis(CDST) has been described as a rare disease with a variety of patho-etiological factors. The diagnosis of CDST is difficult due to various symptoms and signs, none of which is specific to CDST. But timely diagosis is critical for effective management. The introduction and widespread use of computed tomography(CT), magnetic resonance imaging(MRI) and cerebral angiography made early diagnosis of CDST possible. In particular, MR venography is the most useful tool for establishing a correct diagnosis quickly. In early literature, mortality ranked between 30% and 50% but in more recent series it is between 5.5% and 30%. With the advent of diagnostic and therapeutic tools, early diagnosis and proper management has made the prognosis better. The appropriate therapy for CDST, however, has been the subject of much cortroversy. Individual variations of the venous system and collateral vessels are key factors to decide the proper treatment. In this report, we present two cases with symptomatic CDST treated without open surgical or direct endovascular interventions with good outcome.

• The Korean Journal of Pain
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• v.23 no.3
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• pp.211-214
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• 2010

Spontaneous retropharyngeal hematoma is rare and difficult to diagnosis early. A 23-year-old male spontaneously developed acute onset of neck pain, limitation of neck motion, and mild dysphagia. Magnetic resonance imaging demonstrated blood products in prevertebral space from C2 to C4, suggesting a diagnosis of retropharyngeal hematoma. We report a rare case of spontaneous retropharyngeal hematoma causing neck pain.