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  • Open Access

    ARTICLE

    Deep Learning-Driven Anomaly Detection for IoMT-Based Smart Healthcare Systems

    Attiya Khan1, Muhammad Rizwan2, Ovidiu Bagdasar2,3, Abdulatif Alabdulatif4,*, Sulaiman Alamro4, Abdullah Alnajim5

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2121-2141, 2024, DOI:10.32604/cmes.2024.054380 - 31 October 2024

    Abstract The Internet of Medical Things (IoMT) is an emerging technology that combines the Internet of Things (IoT) into the healthcare sector, which brings remarkable benefits to facilitate remote patient monitoring and reduce treatment costs. As IoMT devices become more scalable, Smart Healthcare Systems (SHS) have become increasingly vulnerable to cyberattacks. Intrusion Detection Systems (IDS) play a crucial role in maintaining network security. An IDS monitors systems or networks for suspicious activities or potential threats, safeguarding internal networks. This paper presents the development of an IDS based on deep learning techniques utilizing benchmark datasets. We propose 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

    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

    IoMT-Based Healthcare Framework for Ambient Assisted Living Using a Convolutional Neural Network

    Waleed T. Al-Sit1, Nidal A. Al-Dmour2, Taher M. Ghazal3,4,*, Ghassan F. Issa3

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6867-6878, 2023, DOI:10.32604/cmc.2023.034952 - 28 December 2022

    Abstract In the age of universal computing, human life is becoming smarter owing to the recent developments in the Internet of Medical Things (IoMT), wearable sensors, and telecommunication innovations, which provide more effective and smarter healthcare facilities. IoMT has the potential to shape the future of clinical research in the healthcare sector. Wearable sensors, patients, healthcare providers, and caregivers can connect through an IoMT network using software, information, and communication technology. Ambient assisted living (AAL) allows the incorporation of emerging innovations into the routine life events of patients. Machine learning (ML) teaches machines to learn from More >

  • Open Access

    ARTICLE

    A Secure and Efficient Signature Scheme for IoT in Healthcare

    Latika Kakkar1, Deepali Gupta1, Sarvesh Tanwar2, Sapna Saxena3, Khalid Alsubhi4, Divya Anand5, Irene Delgado Noya6,7, Nitin Goyal1,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6151-6168, 2022, DOI:10.32604/cmc.2022.023769 - 28 July 2022

    Abstract To provide faster access to the treatment of patients, healthcare system can be integrated with Internet of Things to provide prior and timely health services to the patient. There is a huge limitation in the sensing layer as the IoT devices here have low computational power, limited storage and less battery life. So, this huge amount of data needs to be stored on the cloud. The information and the data sensed by these devices is made accessible on the internet from where medical staff, doctors, relatives and family members can access this information. This helps… More >

  • Open Access

    ARTICLE

    IoMT-Enabled Fusion-Based Model to Predict Posture for Smart Healthcare Systems

    Taher M. Ghazal1,2,*, Mohammad Kamrul Hasan1, Siti Norul Huda Abdullah1, Khairul Azmi Abubakkar1, Mohammed A. M. Afifi2

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2579-2597, 2022, DOI:10.32604/cmc.2022.019706 - 07 December 2021

    Abstract Smart healthcare applications depend on data from wearable sensors (WSs) mounted on a patient’s body for frequent monitoring information. Healthcare systems depend on multi-level data for detecting illnesses and consequently delivering correct diagnostic measures. The collection of WS data and integration of that data for diagnostic purposes is a difficult task. This paper proposes an Errorless Data Fusion (EDF) approach to increase posture recognition accuracy. The research is based on a case study in a health organization. With the rise in smart healthcare systems, WS data fusion necessitates careful attention to provide sensitive analysis of… More >

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