Special lssues
Table of Content

IoMT and Smart Healthcare

Submission Deadline: 20 February 2023 (closed)

Guest Editors

Dr. Parul Agarwal, Jamia Hamdard, India.
Prof. M. Afshar Alam, Jamia Hamdard, India.
Dr. Deepika Koundal, University of Petroleum and Energy Studies, India.
Dr. Yanhui Guo, University of Illinois at Springfield, USA.
Dr. Shakir Khan, Imam Mohammad Ibn Saud Islamic University, KSA.


Internet of medical things (IoMT), combines all medical devices, and applications that can gather, analyse, and share data using the Internet. IoMT devices can be used to capture data either on the human body itself or in clinical settings The data captured, and transmitted can then be further used for decision making or for predictive, and diagnostic analysis. This data is captured and then used in cloud-based hosting applications. Since it heavily relies on communication technologies for its function, Thus, connectivity, energy minimization, and cost might be a few hindrances. Smart healthcare heavily relies on IoT, and IoMT devices. Remote patient monitoring, diagnosis, cure, and treatment are mostly sensor -based which gathers data and helps in improving healthcare services.

This special issue is intended to invite research articles/ critical reviews/ case studies from researchers on how IoMT and its related technologies form an integral part of Smart healthcare.


IoT and Cognitive IoT
Remote health monitoring
Electronic health records
Smart hospitals
Connected devices/ healthcare
Data analytics
Biomedical sensors
Wearable sensors
Biomedical informatics
Deep Learning
Machine Learning

Published Papers

  • Open Access


    Detection of Different Stages of Alzheimer’s Disease Using CNN Classifier

    S M Hasan Mahmud, Md Mamun Ali, Mohammad Fahim Shahriar, Fahad Ahmed Al-Zahrani, Kawsar Ahmed, Dip Nandi, Francis M. Bui
    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3933-3948, 2023, DOI:10.32604/cmc.2023.039020
    (This article belongs to this Special Issue: IoMT and Smart Healthcare)
    Abstract Alzheimer’s disease (AD) is a neurodevelopmental impairment that results in a person’s behavior, thinking, and memory loss. The most common symptoms of AD are losing memory and early aging. In addition to these, there are several serious impacts of AD. However, the impact of AD can be mitigated by early-stage detection though it cannot be cured permanently. Early-stage detection is the most challenging task for controlling and mitigating the impact of AD. The study proposes a predictive model to detect AD in the initial phase based on machine learning and a deep learning approach to address the issue. To build… More >

  • Open Access


    Machine Learning-Enabled Communication Approach for the Internet of Medical Things

    Rahim Khan, Abdullah Ghani, Samia Allaoua Chelloug, Mohammed Amin, Aamir Saeed, Jason Teo
    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1569-1584, 2023, DOI:10.32604/cmc.2023.039859
    (This article belongs to this Special Issue: IoMT and Smart Healthcare)
    Abstract The Internet of Medical Things (IoMT) is mainly concerned with the efficient utilisation of wearable devices in the healthcare domain to manage various processes automatically, whereas machine learning approaches enable these smart systems to make informed decisions. Generally, broadcasting is used for the transmission of frames, whereas congestion, energy efficiency, and excessive load are among the common issues associated with existing approaches. In this paper, a machine learning-enabled shortest path identification scheme is presented to ensure reliable transmission of frames, especially with the minimum possible communication overheads in the IoMT network. For this purpose, the proposed scheme utilises a well-known… More >

Share Link