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  • Open Access

    ARTICLE

    Artificial Intelligence in Medicine: Real Time Electronic Stethoscope for Heart Diseases Detection

    Batyrkhan Omarov1,2,*, Nurbek Saparkhojayev2, Shyrynkyz Shekerbekova3, Oxana Akhmetova1, Meruert Sakypbekova1, Guldina Kamalova3, Zhanna Alimzhanova1, Lyailya Tukenova3, Zhadyra Akanova4

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2815-2833, 2022, DOI:10.32604/cmc.2022.019246 - 27 September 2021

    Abstract Diseases of the cardiovascular system are one of the major causes of death worldwide. These diseases could be quickly detected by changes in the sound created by the action of the heart. This dynamic auscultations need extensive professional knowledge and emphasis on listening skills. There is also an unmet requirement for a compact cardiac condition early warning device. In this paper, we propose a prototype of a digital stethoscopic system for the diagnosis of cardiac abnormalities in real time using machine learning methods. This system consists of three subsystems that interact with each other (1)… More >

  • Open Access

    ARTICLE

    Prediction Model for Coronavirus Pandemic Using Deep Learning

    Mamoona Humayun1,*, Ahmed Alsayat2

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 947-961, 2022, DOI:10.32604/csse.2022.019288 - 24 September 2021

    Abstract The recent global outbreak of COVID-19 damaged the world health systems, human health, economy, and daily life badly. None of the countries was ready to face this emerging health challenge. Health professionals were not able to predict its rise and next move, as well as the future curve and impact on lives in case of a similar pandemic situation happened. This created huge chaos globally, for longer and the world is still struggling to come up with any suitable solution. Here the better use of advanced technologies, such as artificial intelligence and deep learning, may… More >

  • Open Access

    ARTICLE

    Big Data Analytics with OENN Based Clinical Decision Support System

    Thejovathi Murari1, L. Prathiba2, Kranthi Kumar Singamaneni3,*, D. Venu4, Vinay Kumar Nassa5, Rachna Kohar6, Satyajit Sidheshwar Uparkar7

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1241-1256, 2022, DOI:10.32604/iasc.2022.020203 - 22 September 2021

    Abstract In recent times, big data analytics using Machine Learning (ML) possesses several merits for assimilation and validation of massive quantity of complicated healthcare data. ML models are found to be scalable and flexible over conventional statistical tools, which makes them suitable for risk stratification, diagnosis, classification and survival prediction. In spite of these benefits, the utilization of ML in healthcare sector faces challenges which necessitate massive training data, data preprocessing, model training and parameter optimization based on the clinical problem. To resolve these issues, this paper presents new Big Data Analytics with Optimal Elman Neural… More >

  • Open Access

    ARTICLE

    ML-Fresh: Novel Routing Protocol in Opportunistic Networks Using Machine Learning

    Puneet Garg*, Ashutosh Dixit, Preeti Sethi

    Computer Systems Science and Engineering, Vol.40, No.2, pp. 703-717, 2022, DOI:10.32604/csse.2022.019557 - 09 September 2021

    Abstract Opportunistic Networks (OppNets) is gaining popularity day-by-day due to their various applications in the real-life world. The two major reasons for its popularity are its suitability to be established without any requirement of additional infrastructure and the ability to tolerate long delays during data communication. Opportunistic Network is also considered as a descendant of Mobile Ad hoc Networks (Manets) and Wireless Sensor Networks (WSNs), therefore, it inherits most of the traits from both mentioned networking techniques. Apart from its popularity, Opportunistic Networks are also starting to face challenges nowadays to comply with the emerging issues of… More >

  • Open Access

    ARTICLE

    Blockchain and Artificial Intelligence Applications to Defeat COVID-19 Pandemic

    Mohammed Baz1, Sabita Khatri2, Abdullah Baz3, Hosam Alhakami4, Alka Agrawal2, Raees Ahmad Khan2,*

    Computer Systems Science and Engineering, Vol.40, No.2, pp. 691-702, 2022, DOI:10.32604/csse.2022.019079 - 09 September 2021

    Abstract The rapid emergence of novel virus named SARS-CoV2 and unchecked dissemination of this virus around the world ever since its outbreak in 2020, provide critical research criteria to assess the vulnerabilities of our current health system. The paper addresses our preparedness for the management of such acute health emergencies and the need to enhance awareness, about public health and healthcare mechanisms. In view of this unprecedented health crisis, distributed ledger and AI technology can be seen as one of the promising alternatives for fighting against such epidemics at the early stages, and with the higher… More >

  • Open Access

    ARTICLE

    An Artificial Intelligence Approach for Solving Stochastic Transportation Problems

    Prachi Agrawal1, Khalid Alnowibet2, Talari Ganesh1, Adel F. Alrasheedi2, Hijaz Ahmad3, Ali Wagdy Mohamed4,5,*

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 817-829, 2022, DOI:10.32604/cmc.2022.019685 - 07 September 2021

    Abstract Recent years witness a great deal of interest in artificial intelligence (AI) tools in the area of optimization. AI has developed a large number of tools to solve the most difficult search-and-optimization problems in computer science and operations research. Indeed, metaheuristic-based algorithms are a sub-field of AI. This study presents the use of the metaheuristic algorithm, that is, water cycle algorithm (WCA), in the transportation problem. A stochastic transportation problem is considered in which the parameters supply and demand are considered as random variables that follow the Weibull distribution. Since the parameters are stochastic, the… More >

  • Open Access

    ARTICLE

    Artificial Intelligence Based Reliable Load Balancing Framework in Software-Defined Networks

    Mohammad Riyaz Belgaum1, Fuead Ali1, Zainab Alansari2, Shahrulniza Musa1,*, Muhammad Mansoor Alam1,3, M. S. Mazliham4

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 251-266, 2022, DOI:10.32604/cmc.2022.018211 - 07 September 2021

    Abstract Software-defined networking (SDN) plays a critical role in transforming networking from traditional to intelligent networking. The increasing demand for services from cloud users has increased the load on the network. An efficient system must handle various loads and increasing needs representing the relationships and dependence of businesses on automated measurement systems and guarantee the quality of service (QoS). The multiple paths from source to destination give a scope to select an optimal path by maintaining an equilibrium of load using some best algorithms. Moreover, the requests need to be transferred to reliable network elements. To… More >

  • Open Access

    ARTICLE

    Design of an Information Security Service for Medical Artificial Intelligence

    Yanghoon Kim1, Jawon Kim2, Hangbae Chang3,*

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 679-694, 2022, DOI:10.32604/cmc.2022.015610 - 07 September 2021

    Abstract The medical convergence industry has gradually adopted ICT devices, which has led to legacy security problems related to ICT devices. However, it has been difficult to solve these problems due to data resource issues. Such problems can cause a lack of reliability in medical artificial intelligence services that utilize medical information. Therefore, to provide reliable services focused on security internalization, it is necessary to establish a medical convergence environment-oriented security management system. This study proposes the use of system identification and countermeasures to secure system reliability when using medical convergence environment information in medical artificial More >

  • Open Access

    ARTICLE

    Deep Learning-Based Skin Lesion Diagnosis Model Using Dermoscopic Images

    G. Reshma1,*, Chiai Al-Atroshi2, Vinay Kumar Nassa3, B.T. Geetha4, Gurram Sunitha5, Mohammad Gouse Galety6, S. Neelakandan7

    Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 621-634, 2022, DOI:10.32604/iasc.2022.019117 - 03 September 2021

    Abstract In recent years, intelligent automation in the healthcare sector becomes more familiar due to the integration of artificial intelligence (AI) techniques. Intelligent healthcare systems assist in making better decisions, which further enable the patient to provide improved medical services. At the same time, skin lesion is a deadly disease that affects people of all age groups. Skin lesion segmentation and classification play a vital part in the earlier and precise skin cancer diagnosis by intelligent systems. However, the automated diagnosis of skin lesions in dermoscopic images is challenging because of the problems such as artifacts… More >

  • Open Access

    ARTICLE

    Implementation of Artificial Intelligence Based Analyzer Using Multi-Agent System Approach

    Norah S. Farooqi1, Mohamed O. Khozium2,*

    Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 297-309, 2022, DOI:10.32604/iasc.2022.019060 - 03 September 2021

    Abstract Using Business Intelligence (BI) applications is a critical factor for modern enterprises’ success. BI is one of the key components that persistently required for the modern high-tech companies and industries were used to handle huge amounts of data in every minute of the operations. The existing literature suggested that the lack of dynamic decision making, accuracy, and the degree of flexibility are the key limitations for handling the operational data. Many industries and companies adopted the software-based solution; however, the intelligence is there due to the dependence of the operational engagement for each of the… More >

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