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Call for papers - Sensor informatics and disease prediction

Guest Editors  

Fazlullah Khan, PhD, Department of Computer Science, Faculty of Science and Engineering, University of Nottingham Ningbo, China 
Imran Razzak, PhD, School of Computer Science and Engineering, University of New South Wales, Australia
T Poongodi, PhD, School of Computing Science and Engineering, Galgotias University, India
Varun G Menon, PhD, SCMS School of Engineering and Technology, India

Submission Status: Open   |   Submission Deadline: 25 July 2024


BMC Medical Informatics and Decision Making is calling for submissions to our Collection on Sensor informatics and disease prediction. This collection welcomes submissions on novel developments in the field of sensor informatics, for disease prevention and health risk assessment, early disease detection, and monitoring of chronic diseases. Any technical advancement for the acquisition, processing, use, and retrieval of wearable sensor-collected biomedical data will be also considered.

Meet the Guest Editors

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Fazlullah Khan, PhD, Department of Computer Science, Faculty of Science and Engineering, University of Nottingham Ningbo, China

Fazlullah Khan works at the Department of Computer Science, Nottingham University Ningbo China. He has been working in academia and industry since 2011 on sensing technologies. His research interests are Intelligent and robust protocol designs, IoT, Machine Learning, Artificial Intelligence, Data Analytics, and Health Informatics. His research has been published in IEEE TII, IEEE IoT, IEEE TNSE, TCSS, TGCN, ITS, Elsevier FGCS, JNCA, Springer NCAA, and MONET. He has served as Guest Editor of the IEEE JBHI, SMCM, TCE, Elsevier DCAN, Springer NCAA, and MONET. He has served over 10 conferences in leadership capacities including General Chair and Co-Chair.

Imran Razzak, PhD, School of Computer Science and Engineering, University of New South Wales, Australia

Imran Razzak works at the School of Computer Science and Engineering, University of New South Wales, Australia. His area of research includes connecting language and vision for better interpretation of multidimensional data and spans three broad areas: Machine Learning, Computer Vision, and Natural Language Processing with special emphasis on healthcare and the use of natural language to explain the rationale and decision-making process behind the use of machine learning algorithms and models. He has published more than 200 research articles in top-notch venues and served as Guest Editor of the IEEE JBHI, SMCM, TCE, TII, TCSS, and Springer Nature.

T Poongodi, PhD, School of Computing Science and Engineering, Galgotias University, India

T Poongodi is currently working as a Professor in the School of Computing Science & Engineering at the Galgotias University, Delhi – NCR, India. She has published 50+ book chapters, 15+ authored/edited books and 30+ international journals and conferences in the areas of Internet of Things, Data Analytics, Blockchain Technology, Artificial Intelligence, Machine Learning, and Healthcare Informatics, published by reputed publishers such as Springer, Elsevier, IET, Wiley, De-Gruyter, CRC Taylor & Francis, and Apple Academic Press. She received awards namely the Research and Innovation award (2019, 2020, 2021), from Galgotias University.

Varun G Menon, PhD, SCMS School of Engineering and Technology, India

Varun G Menon is currently a Professor and Head of the Department of Computer Science Engineering, and International Collaborations in charge at SCMS School of Engineering and Technology, India. He is a Distinguished Speaker of ACM and a Senior Member of IEEE. He is currently an associate editor of Physical Communications, IET Networks, IET Quantum Communications, series editor of IEEE Transactions on Intelligent Transportation Systems, technical editor of Computer Communications. His research interests include Sensor Technologies, Artificial Intelligence, Internet of Things, Green IoT, Wireless Communication, Fog Computing and Networking.

About the Collection

BMC Medical Informatics and Decision Making is calling for submissions to our Collection on Sensor informatics and disease prediction. Wearable technology can be used to collect health related data and make clinical decisions for patient safety and disease management. The analysis and management of data collected through wearable technologies presents challenges such as interoperability and advanced data analytics. As the use of remote healthcare services keeps growing, sensor informatics aims to address these challenges.

This collection welcomes submissions on novel developments in the field of sensor informatics, for disease prevention and health risk assessment, early disease detection, and monitoring of chronic diseases. Any technical advancement for the acquisition, processing, use, and retrieval of wearable sensor-collected biomedical data will be also considered.


Image credit: metamorworks/ Getty Images_iStock

  1. Electrocardiogram (ECG) signals are very important for heart disease diagnosis. In this paper, a novel early prediction method based on Nested Long Short-Term Memory (Nested LSTM) is developed for sudden cardi...

    Authors: Ke Wang, Kai Zhang, Banteng Liu, Wei Chen and Meng Han
    Citation: BMC Medical Informatics and Decision Making 2024 24:94
    Content type: Research Published on:

  2. Emerging from the convergence of digital twin technology and the metaverse, consumer health (MCH) is witnessing a transformative shift. The amalgamation of bioinformatics with healthcare Big Data has ushered i...

    Authors: Chaitanya Kulkarni, Aadam Quraishi, Mohan Raparthi, Mohammad Shabaz, Muhammad Attique Khan, Raj A. Varma, Ismail Keshta, Mukesh Soni and Haewon Byeon
    Citation: BMC Medical Informatics and Decision Making 2024 24:92
    Content type: Research Published on:

  3. Traditionally, existing studies assessing the health associations of accelerometer-measured movement behaviors have been performed with few averaged values, mainly representing the duration of physical activit...

    Authors: Vahid Farrahi, Paul J Collings and Mourad Oussalah
    Citation: BMC Medical Informatics and Decision Making 2024 24:74
    Content type: Research Published on:

Submission Guidelines

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This Collection welcomes submission of original Research Articles. Should you wish to submit a different article type, please read our submission guidelines to confirm that type is accepted by the journal. Articles for this Collection should be submitted via our submission system, Snapp. During the submission process you will be asked whether you are submitting to a Collection, please select "Sensor informatics and disease prediction" from the dropdown menu.

Articles will undergo the journal’s standard peer-review process and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.

The Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Editors have competing interests is handled by another Editorial Board Member who has no competing interests.