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  • Open Access

    ARTICLE

    Improving Thyroid Disorder Diagnosis via Ensemble Stacking and Bidirectional Feature Selection

    Muhammad Armghan Latif1, Zohaib Mushtaq2, Saad Arif3, Sara Rehman4, Muhammad Farrukh Qureshi5, Nagwan Abdel Samee6, Maali Alabdulhafith6,*, Yeong Hyeon Gu7, Mohammed A. Al-masni7

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4225-4241, 2024, DOI:10.32604/cmc.2024.047621 - 26 March 2024

    Abstract Thyroid disorders represent a significant global health challenge with hypothyroidism and hyperthyroidism as two common conditions arising from dysfunction in the thyroid gland. Accurate and timely diagnosis of these disorders is crucial for effective treatment and patient care. This research introduces a comprehensive approach to improve the accuracy of thyroid disorder diagnosis through the integration of ensemble stacking and advanced feature selection techniques. Sequential forward feature selection, sequential backward feature elimination, and bidirectional feature elimination are investigated in this study. In ensemble learning, random forest, adaptive boosting, and bagging classifiers are employed. The effectiveness of… More >

  • Open Access

    ARTICLE

    Smart Healthcare Activity Recognition Using Statistical Regression and Intelligent Learning

    K. Akilandeswari1, Nithya Rekha Sivakumar2,*, Hend Khalid Alkahtani3, Shakila Basheer3, Sara Abdelwahab Ghorashi2

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1189-1205, 2024, DOI:10.32604/cmc.2023.034815 - 30 January 2024

    Abstract In this present time, Human Activity Recognition (HAR) has been of considerable aid in the case of health monitoring and recovery. The exploitation of machine learning with an intelligent agent in the area of health informatics gathered using HAR augments the decision-making quality and significance. Although many research works conducted on Smart Healthcare Monitoring, there remain a certain number of pitfalls such as time, overhead, and falsification involved during analysis. Therefore, this paper proposes a Statistical Partial Regression and Support Vector Intelligent Agent Learning (SPR-SVIAL) for Smart Healthcare Monitoring. At first, the Statistical Partial Regression… More >

  • Open Access

    ARTICLE

    Enhancing Healthcare Data Security and Disease Detection Using Crossover-Based Multilayer Perceptron in Smart Healthcare Systems

    Mustufa Haider Abidi*, Hisham Alkhalefah, Mohamed K. Aboudaif

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 977-997, 2024, DOI:10.32604/cmes.2023.044169 - 30 December 2023

    Abstract The healthcare data requires accurate disease detection analysis, real-time monitoring, and advancements to ensure proper treatment for patients. Consequently, Machine Learning methods are widely utilized in Smart Healthcare Systems (SHS) to extract valuable features from heterogeneous and high-dimensional healthcare data for predicting various diseases and monitoring patient activities. These methods are employed across different domains that are susceptible to adversarial attacks, necessitating careful consideration. Hence, this paper proposes a crossover-based Multilayer Perceptron (CMLP) model. The collected samples are pre-processed and fed into the crossover-based multilayer perceptron neural network to detect adversarial attacks on the medical… More >

  • Open Access

    ARTICLE

    A Novel Edge-Assisted IoT-ML-Based Smart Healthcare Framework for COVID-19

    Mahmood Hussain Mir1,*, Sanjay Jamwal1, Ummer Iqbal2, Abolfazl Mehbodniya3, Julian Webber3, Umar Hafiz Khan4

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2529-2565, 2023, DOI:10.32604/cmes.2023.027173 - 03 August 2023

    Abstract The lack of modern technology in healthcare has led to the death of thousands of lives worldwide due to COVID- 19 since its outbreak. The Internet of Things (IoT) along with other technologies like Machine Learning can revolutionize the traditional healthcare system. Instead of reactive healthcare systems, IoT technology combined with machine learning and edge computing can deliver proactive and preventive healthcare services. In this study, a novel healthcare edge-assisted framework has been proposed to detect and prognosticate the COVID-19 suspects in the initial phases to stop the transmission of coronavirus infection. The proposed framework… More >

  • Open Access

    ARTICLE

    IoMT-Based Smart Healthcare of Elderly People Using Deep Extreme Learning Machine

    Muath Jarrah1, Hussam Al Hamadi4,*, Ahmed Abu-Khadrah2, Taher M. Ghazal1,3

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 19-33, 2023, DOI:10.32604/cmc.2023.032775 - 08 June 2023

    Abstract The Internet of Medical Things (IoMT) enables digital devices to gather, infer, and broadcast health data via the cloud platform. The phenomenal growth of the IoMT is fueled by many factors, including the widespread and growing availability of wearables and the ever-decreasing cost of sensor-based technology. There is a growing interest in providing solutions for elderly people living assistance in a world where the population is rising rapidly. The IoMT is a novel reality transforming our daily lives. It can renovate modern healthcare by delivering a more personalized, protective, and collaborative approach to care. However, More >

  • Open Access

    ARTICLE

    BIoMT: A Blockchain-Enabled Healthcare Architecture for Information Security in the Internet of Medical Things

    Sahar Badri1, Sana Ullah Jan2,*, Daniyal Alghazzawi1, Sahar Aldhaheri1, Nikolaos Pitropakis2

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3667-3684, 2023, DOI:10.32604/csse.2023.037531 - 03 April 2023

    Abstract Rapid technological advancement has enabled modern healthcare systems to provide more sophisticated and real-time services on the Internet of Medical Things (IoMT). The existing cloud-based, centralized IoMT architectures are vulnerable to multiple security and privacy problems. The blockchain-enabled IoMT is an emerging paradigm that can ensure the security and trustworthiness of medical data sharing in the IoMT networks. This article presents a private and easily expandable blockchain-based framework for the IoMT. The proposed framework contains several participants, including private blockchain, hospital management systems, cloud service providers, doctors, and patients. Data security is ensured by incorporating More >

  • Open Access

    ARTICLE

    Heap Based Optimization with Deep Quantum Neural Network Based Decision Making on Smart Healthcare Applications

    Iyad Katib1, Mahmoud Ragab2,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3749-3765, 2023, DOI:10.32604/csse.2023.036796 - 03 April 2023

    Abstract The concept of smart healthcare has seen a gradual increase with the expansion of information technology. Smart healthcare will use a new generation of information technologies, like artificial intelligence, the Internet of Things (IoT), cloud computing, and big data, to transform the conventional medical system in an all-around way, making healthcare highly effective, more personalized, and more convenient. This work designs a new Heap Based Optimization with Deep Quantum Neural Network (HBO-DQNN) model for decision-making in smart healthcare applications. The presented HBO-DQNN model majorly focuses on identifying and classifying healthcare data. In the presented HBO-DQNN… More >

  • Open Access

    ARTICLE

    A Framework for Securing Saudi Arabian Hospital Industry: Vision-2030 Perspective

    Hosam Alhakami1,*, Abdullah Baz2, Mohammad Al-shareef3, Rajeev Kumar4, Alka Agrawal5, Raees Ahmad Khan5

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2773-2786, 2023, DOI:10.32604/iasc.2023.021560 - 15 March 2023

    Abstract Recent transformation of Saudi Arabian healthcare sector into a revenue producing one has signaled several advancements in healthcare in the country. Transforming healthcare management into Smart hospital systems is one of them. Secure hospital management systems which are breach-proof only can be termed as effective smart hospital systems. Given the perspective of Saudi Vision-2030, many practitioners are trying to achieve a cost-effective hospital management system by using smart ideas. In this row, the proposed framework posits the main objectives for creating smart hospital management systems that can only be acknowledged by managing the security of healthcare… More >

  • Open Access

    ARTICLE

    Teamwork Optimization with Deep Learning Based Fall Detection for IoT-Enabled Smart Healthcare System

    Sarah B. Basahel1, Saleh Bajaba2, Mohammad Yamin3, Sachi Nandan Mohanty4, E. Laxmi Lydia5,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1353-1369, 2023, DOI:10.32604/cmc.2023.036453 - 06 February 2023

    Abstract The current advancement in cloud computing, Artificial Intelligence (AI), and the Internet of Things (IoT) transformed the traditional healthcare system into smart healthcare. Healthcare services could be enhanced by incorporating key techniques like AI and IoT. The convergence of AI and IoT provides distinct opportunities in the medical field. Fall is regarded as a primary cause of death or post-traumatic complication for the ageing population. Therefore, earlier detection of older person falls in smart homes is required to improve the survival rate of an individual or provide the necessary support. Lately, the emergence of IoT,… More >

  • Open Access

    ARTICLE

    An Immutable Framework for Smart Healthcare Using Blockchain Technology

    Faneela1, Muazzam A. Khan1, Suliman A. Alsuhibany2,*, Walid El-Shafai3,4, Mujeeb Ur Rehman5, Jawad Ahmad6

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 165-179, 2023, DOI:10.32604/csse.2023.035066 - 20 January 2023

    Abstract The advancements in sensing technologies, information processing, and communication schemes have revolutionized the healthcare sector. Electronic Healthcare Records (EHR) facilitate the patients, doctors, hospitals, and other stakeholders to maintain valuable data and medical records. The traditional EHRs are based on cloud-based architectures and are susceptible to multiple cyberattacks. A single attempt of a successful Denial of Service (DoS) attack can compromise the complete healthcare system. This article introduces a secure and immutable blockchain-based framework for the Internet of Medical Things (IoMT) to address the stated challenges. The proposed architecture is on the idea of a More >

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