Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (93)
  • Open Access

    ARTICLE

    Automated Deep Learning Based Cardiovascular Disease Diagnosis Using ECG Signals

    S. Karthik1, M. Santhosh1,*, M. S. Kavitha1, A. Christopher Paul2

    Computer Systems Science and Engineering, Vol.42, No.1, pp. 183-199, 2022, DOI:10.32604/csse.2022.021698 - 02 December 2021

    Abstract Automated biomedical signal processing becomes an essential process to determine the indicators of diseased states. At the same time, latest developments of artificial intelligence (AI) techniques have the ability to manage and analyzing massive amounts of biomedical datasets results in clinical decisions and real time applications. They can be employed for medical imaging; however, the 1D biomedical signal recognition process is still needing to be improved. Electrocardiogram (ECG) is one of the widely used 1-dimensional biomedical signals, which is used to diagnose cardiovascular diseases. Computer assisted diagnostic models find it difficult to automatically classify the… More >

  • Open Access

    ARTICLE

    Heart Sound Analysis for Abnormality Detection

    Zainab Arshad1, Sohail Masood Bhatti2,*, Huma Tauseef3, Arfan Jaffar2

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1195-1205, 2022, DOI:10.32604/iasc.2022.022160 - 17 November 2021

    Abstract According to the World Health Organization, 31% death rate in the World is because of cardiovascular diseases like heart arrhythmia and heart failure. Early diagnosis of heart problems may help in timely treatment of the patients and hence control death rate. Heart sounds are good signals of heart health if examined by an expert. Moreover, heart sounds can be analyzed with inexpensive and portable medical devices. Automatic heart sound classification can be very useful in diagnosing heart problems. Major focus of this research is to study the existing techniques for heart sound classification and develop More >

  • Open Access

    ARTICLE

    Cardiovascular Disease Prediction Among the Malaysian Cohort Participants Using Electrocardiogram

    Mohd Zubir Suboh1,2, Nazrul Anuar Nayan1,3,*, Noraidatulakma Abdullah4,5, Nurul Ain Mhd Yusof4, Mariatul Akma Hamid4, Azwa Shawani Kamalul Arinfin4, Syakila Mohd Abd Daud4, Mohd Arman Kamaruddin4, Rosmina Jaafar1, Rahman Jamal4

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1111-1132, 2022, DOI:10.32604/cmc.2022.022123 - 03 November 2021

    Abstract A comprehensive study was conducted to differentiate cardiovascular disease (CVD) subjects from non-CVD subjects using short recording electrocardiogram (ECG) of 244 Malaysian adults in The Malaysian Cohort project. An automated peak detection algorithm to detect nine fiducial points of electrocardiogram (ECG) was developed. Forty-eight features were extracted in both time and frequency domains, including statistical features obtained from heart rate variability and Poincare plot analysis. These include five new features derived from spectrum counts of five different frequency ranges. Feature selection was then made based on p-value and correlation matrix. Selected features were used as… More >

  • Open Access

    ARTICLE

    Intelligent Biomedical Electrocardiogram Signal Processing for Cardiovascular Disease Diagnosis

    R. Krishnaswamy1,*, B. Sivakumar2, B. Viswanathan3, Fahd N. Al-Wesabi4,5, Marwa Obayya6, Anwer Mustafa Hilal7

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 255-268, 2022, DOI:10.32604/cmc.2022.021995 - 03 November 2021

    Abstract Automatic biomedical signal recognition is an important process for several disease diagnoses. Particularly, Electrocardiogram (ECG) is commonly used to identify cardiovascular diseases. The professionals can determine the existence of cardiovascular diseases using the morphological patterns of the ECG signals. In order to raise the diagnostic accuracy and reduce the diagnostic time, automated computer aided diagnosis model is necessary. With the advancements of artificial intelligence (AI) techniques, large quantity of biomedical datasets can be easily examined for decision making. In this aspect, this paper presents an intelligent biomedical ECG signal processing (IBECG-SP) technique for CVD diagnosis.… More >

  • Open Access

    ARTICLE

    Prediction of Cardiovascular Disease Using Machine Learning Technique—A Modern Approach

    Visvasam Devadoss Ambeth Kumar1, Chetan Swarup2, Indhumathi Murugan1, Abhishek Kumar3, Kamred Udham Singh4, Teekam Singh5, Ramu Dubey6,*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 855-869, 2022, DOI:10.32604/cmc.2022.021582 - 03 November 2021

    Abstract Cardio Vascular disease (CVD), involving the heart and blood vessels is one of the most leading causes of death throughout the world. There are several risk factors for causing heart diseases like sedentary lifestyle, unhealthy diet, obesity, diabetes, hypertension, smoking and consumption of alcohol, stress, hereditary factory etc. Predicting cardiovascular disease and improving and treating the risk factors at an early stage are of paramount importance to save the precious life of a human being. At present, the highly stressful life with bad lifestyle activities causes heart disease at a very young age. The main… More >

  • Open Access

    ARTICLE

    Heart Failure Patient Survival Analysis with Multi Kernel Support Vector Machine

    R. Sujatha1, Jyotir Moy Chatterjee2, NZ Jhanjhi3, Thamer A. Tabbakh4, Zahrah A. Almusaylim5,*

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 115-129, 2022, DOI:10.32604/iasc.2022.019133 - 26 October 2021

    Abstract Heart failure (HF) is an intercontinental pandemic influencing in any event 26 million individuals globally and is expanding in commonness. HF healthiness consumptions are extensive and will increment significantly with a maturing populace. As per the World Health Organization (WHO), Cardiovascular diseases (CVDs) are the major reason for all-inclusive death, taking an expected 17.9 million lives per year. CVDs are a class of issues of the heart, blood vessels and include coronary heart sickness, cerebrovascular illness, rheumatic heart malady, and various other conditions. In the medical care industry, a lot of information is as often… More >

  • Open Access

    REVIEW

    Understanding the role of miRNAs in the pathogenesis of brain arteriovenous malformations

    ILGIZ GAREEV1, OZAL BEYLERLI1, CHUNLEI WANG2,3, ANDREI SOKHATSKII2,3, YANCHAO LIANG2,3, HUAN XIANG2,3, CHUNYANG LIU2,3, XUN XU2,3, YANG GUANG2,3

    BIOCELL, Vol.46, No.1, pp. 27-35, 2022, DOI:10.32604/biocell.2022.016288 - 28 September 2021

    Abstract Brain arteriovenous malformations (AVMs) are abnormal vessels that are prone to rupture, causing life-threatening intracerebral hemorrhage (ICH). Understanding the molecular basis of pathogenesis, timely diagnosis, and treatment of brain AVMs are some of the urgent problems in neurosurgery. MicroRNAs (miRNAs) are small endogenous RNAs that regulate gene-expression posttranscriptionally. MiRNAs are involved in almost all biological processes, including cell proliferation, apoptosis, and cell differentiation. Recent studies have shown that miRNAs can be involved in brain AVMs formation and rupture. There are also extracellular forms of miRNAs. Circulating miRNAs have been detected in the blood circulation and More >

  • Open Access

    ARTICLE

    Recent Techniques for Harvesting Energy from the Human Body

    Nidal M. Turab1, Hamza Abu Owida2, Jamal I. Al-Nabulsi2,*, Mwaffaq Abu-Alhaija1

    Computer Systems Science and Engineering, Vol.40, No.1, pp. 167-177, 2022, DOI:10.32604/csse.2022.017973 - 26 August 2021

    Abstract The human body contains a near-infinite supply of energy in chemical, thermal, and mechanical forms. However, the majority of implantable and wearable devices are still operated by batteries, whose insufficient capacity and large size limit their lifespan and increase the risk of hazardous material leakage. Such energy can be used to exceed the battery power limits of implantable and wearable devices. Moreover, novel materials and fabrication methods can be used to create various medical therapies and life-enhancing technologies. This review paper focuses on energy-harvesting technologies used in medical and health applications, primarily power collectors from More >

  • Open Access

    ARTICLE

    An Intelligent Forwarding Strategy in SDN-Enabled Named-Data IoV

    Asadullah Tariq1, Irfan ud din1, Rana Asif Rehman2, Byung-Seo Kim3,*

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 2949-2966, 2021, DOI:10.32604/cmc.2021.017658 - 24 August 2021

    Abstract Internet of Vehicles (IoV), a rapidly growing technology for efficient vehicular communication and it is shifting the trend of traditional Vehicular Ad Hoc Networking (VANET) towards itself. The centralized management of IoV endorses its uniqueness and suitability for the Intelligent Transportation System (ITS) safety applications. Named Data Networking (NDN) is an emerging internet paradigm that fulfills most of the expectations of IoV. Limitations of the current IP internet architecture are the main motivation behind NDN. Software-Defined Networking (SDN) is another emerging networking paradigm of technology that is highly capable of efficient management of overall networks… More >

  • Open Access

    ARTICLE

    Segmentation of the Left Ventricle in Cardiac MRI Using Random Walk Techniques

    Osama S. Faragallah1,*, Ghada Abdel-Aziz2, Hala S. El-sayed3, Gamal G. N. Geweid4,5

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 575-588, 2021, DOI:10.32604/iasc.2021.019023 - 11 August 2021

    Abstract As a regular tool for assessing and diagnosing cardiovascular disease (CVD), medical professionals and health care centers, are highly dependent on cardiac imaging. The purpose of dividing the cardiac images is to paint the inner and outer walls of the heart to divide all or part of the limb’s boundaries. In order to enhance cardiologist in the process of cardiac segmentation, new and accurate methods are needed to divide the selected object, which is the left ventricle (LV). Segmentation techniques aim to provide a fast segmentation process and improve the reliability of the process. In… More >

Displaying 41-50 on page 5 of 93. Per Page