Intelligent Telehealth Monitoring with Man-Computer Interface

Submission Deadline: 25 January 2023 (closed)

Guest Editors

Dr. Muhammad Attique Khan, HITEC University, Pakistan
Dr. Shuihua Wang, University of Leicester, UK
Dr. Syed Ahmad Chan Bukhari, St. John's University, USA


Recently, the computerized scheme supported disease diagnosis is common in hospitals. These methods are employed for; disease screening, pre/post-processing, knowledge extraction from the data, disease prediction, treatment planning, execution, and recovery monitoring. The advanced disease diagnosis involves employing advanced procedures, like the body-area network to collect the information, multi-sensor and multi-data collection during the screening, data assessment using modern computer algorithms, and Artificial Intelligence (AI) schemes for efficient data sharing, storage, and retrieval with modern methods.

In the current era, advanced data handling methods, like big data processing, medical cloud-supported data handling, and blockchain, are commonly adopted in modern hospitals to support effective data processing and disease handling. Further, the recently developed man-computer interface (MCI) schemes will support virtual-reality approaches, telehealth monitoring and patient care, internet of things-based data handling and treatment, and precision medicine to ensure the appropriate treatment for the patient. Integrating these modern schemes will create an efficient environment in which the patient-computer and computer-doctor integration is effectively utilized to implement real-time patient monitoring from a remote location.

This special issue focuses on collecting the current research works related to medical data assessment with the man-computer interface from the scientists and researchers. This special issue also welcomes real clinical works and review works from the doctors.


• Skin cancer diagnosis using big data
• Block chain technology for skin cancer diagnosis
• Medical cloud support system for skin cancer in dermoscopic images
• Brain tumor classification using big data and medical cloud
• Breast cancer diagnosis based on Big data and block chain
• Gastrointestinal diseases 
• Covid19 classification using Big Data
• IoT and block chain technology for medical cancer diagnosis
• MCI based breast cancer diagnosis and recognition
• Skin cancer diagnosis using MCI
• MCI based radiologists cancer diagnosis
• MCI based brain tumor diagnosis and classification

Published Papers

  • Open Access


    Artificial Intelligence Based Sentence Level Sentiment Analysis of COVID-19

    Sundas Rukhsar, Mazhar Javed Awan, Usman Naseem, Dilovan Asaad Zebari, Mazin Abed Mohammed, Marwan Ali Albahar, Mohammed Thanoon, Amena Mahmoud
    Computer Systems Science and Engineering, Vol.47, No.1, pp. 791-807, 2023, DOI:10.32604/csse.2023.038384
    (This article belongs to this Special Issue: Intelligent Telehealth Monitoring with Man-Computer Interface)
    Abstract Web-blogging sites such as Twitter and Facebook are heavily influenced by emotions, sentiments, and data in the modern era. Twitter, a widely used microblogging site where individuals share their thoughts in the form of tweets, has become a major source for sentiment analysis. In recent years, there has been a significant increase in demand for sentiment analysis to identify and classify opinions or expressions in text or tweets. Opinions or expressions of people about a particular topic, situation, person, or product can be identified from sentences and divided into three categories: positive for good, negative for bad, and neutral for… More >

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