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  • Open Access

    ARTICLE

    Optimized Identification with Severity Factors of Gastric Cancer for Internet of Medical Things

    Kamalrulnizam Bin Abu Bakar1, Fatima Tul Zuhra2,*, Babangida Isyaku1,3, Fuad A. Ghaleb1

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 785-798, 2023, DOI:10.32604/cmc.2023.034540 - 06 February 2023

    Abstract The Internet of Medical Things (IoMT) emerges with the vision of the Wireless Body Sensor Network (WBSN) to improve the health monitoring systems and has an enormous impact on the healthcare system for recognizing the levels of risk/severity factors (premature diagnosis, treatment, and supervision of chronic disease i.e., cancer) via wearable/electronic health sensor i.e., wireless endoscopic capsule. However, AI-assisted endoscopy plays a very significant role in the detection of gastric cancer. Convolutional Neural Network (CNN) has been widely used to diagnose gastric cancer based on various feature extraction models, consequently, limiting the identification and categorization… More >

  • Open Access

    ARTICLE

    Secured ECG Signal Transmission Using Optimized EGC with Chaotic Neural Network in WBSN

    Ishani Mishra1,*, Sanjay Jain2, Vivek Maik3

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1109-1123, 2023, DOI:10.32604/csse.2023.025999 - 15 June 2022

    Abstract In wireless body sensor network (WBSN), the set of electrocardiogram (ECG) data which is collected from sensor nodes and transmitted to the server remotely supports the experts to monitor the health of a patient. While transmitting these collected data some adversaries may capture and misuse it due to the compromise of security. So, the major aim of this work is to enhance secure transmission of ECG signal in WBSN. To attain this goal, we present Pity Beetle Swarm Optimization Algorithm (PBOA) based Elliptic Galois Cryptography (EGC) with Chaotic Neural Network. To optimize the key generation More >

  • Open Access

    ARTICLE

    Optimized Compressive Sensing Based ECG Signal Compression and Reconstruction

    Ishani Mishra1,*, Sanjay Jain2

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 415-428, 2022, DOI:10.32604/iasc.2022.022860 - 05 January 2022

    Abstract In wireless body sensor network (WBSN), the set of electrocardiograms (ECG) data which is collected from sensor nodes and transmitted to the server remotely supports the experts to monitor the health of a patient. However, due to the size of the ECG data, the performance of the signal compression and reconstruction is degraded. For efficient wireless transmission of ECG data, compressive sensing (CS) frame work plays significant role recently in WBSN. So, this work focuses to present CS for ECG signal compression and reconstruction. Although CS minimizes mean square error (MSE), compression rate and reconstruction More >

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