IEEE Journal of Biomedical and Health Informatics publishes original papers describing recent advances in the field of biomedical and health informatics where information and communication technologies intersect with health, healthcare, life sciences and biomedicine. Papers must contain original content in theoretical analysis, methods, technical development, and/or novel clinical applications of information systems. Topics covered by J-BHI include but are not limited to: acquisition, transmission, storage, retrieval, management, processing and analysis of biomedical and health information; applications of information and communication technologies in the practice of healthcare, public health, patient monitoring, preventive care, early diagnosis of diseases, discovery of new therapies, and patient specific treatment protocols leading to improved outcomes; and the integration of electronic medical and health records, methods of longitudinal data analysis, data mining and discovery tools. Manuscripts may deal with these applications and their integration, such as clinical information systems, decision support systems, medical and biological imaging informatics, wearable systems, body area/sensor networks, informatics in biological and physiological systems, personalized and pervasive health technologies (u-, p-, m- and e-Health), telemedicine, home healthcare and wellness management. Topics related to integration include interoperability, protocol-based patient care, evidence-based medicine, and methods of secure patient data.

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The articles in this journal are peer reviewed in accordance with the requirements set forth in the IEEE PSPB Operations Manual (sections 8.2.1.C & 8.2.2.A). Each published article was reviewed by a minimum of two independent reviewers using a single-blind peer review process, where the identities of the reviewers are not known to the authors, but the reviewers know the identities of the authors. Articles will be screened for plagiarism before acceptance.

Corresponding authors from low-income countries are eligible for waived or reduced open access APCs.

Special Issue on Artificial Intelligence-enabled translational mental healthcare and cognitive neuroscience
Submission Date: 2025-05-30

Mental health and neurological disorders are significant global health concerns, and the complexity of these disorders
necessitates innovative approaches for diagnosis and treatment. AI technology has a promising role for the
transformation of mental healthcare and its pitfalls. The integration of AI-based computational techniques with the
cognitive science offers promising solutions to address these challenges. Given the increasing prevalence of these
disorders and the growing interest in computational neuroscience, this special issue is both important and timely.
Currently, the world faces a critical transformation in the fourth industrial age, called digital revolution, that distinguished
by the integration of different technology types. Accordingly, this special issue aims to bridge the gap between AI and
cognitive neuroscience to facilitate the translation toward the clinical practice applications. It fills the gap in the current
coverage of other related journals by focusing specifically on the application of computational approaches to mental
healthcare and neurological disorders. While existing literature may touch on aspects of these topics, this special issue
provides a comprehensive overview of the latest advancements and methodologies in this area, thereby complementing
and expanding the existing body of knowledge with highlighting the impactful role of AI in clinical practice for mental
healthcare.

This special issue aligns closely with the focus of the JBHI on Cognitive Neuroscience, which emphasizes understanding
of the brain function and dysfunction. By showcasing the latest advances in AI and the computational approaches for
mental healthcare and neurological disorders services, it contributes to the journal's mission of advancing knowledge in
cognitive neuroscience and related fields.

Topics of interest include, but are not limited to, the following:
• AI-based cognitive neuroscience
• Cognitive dysfunction in depression
• Medical image processing of neuroimaging
• Personalized treatment planning in epilepsy
• Data analytics for diagnosis of neurological disease
• Computational techniques for early prognosis of schizophrenia
• Predictive modelling for early detection of mental health disorders
• Artificial Intelligent in Alzheimer’s disease detection and prediction
• Implementation of AI in cognitive neuroscience and mental healthcare
• Computational approaches for cognitive deficits in Alzheimer's disease
• Computational analysis to identify neural signatures in bipolar disorder
• Computational models of anxiety disorders for improved understanding
• Artificial intelligence for big data analysis in mental health applications
• Computational tools for personalized diagnosis in neurological disorders
• Artificial intelligence in prediction and diagnosis of neurological disorders
• Computational neuroimaging analysis for biomarkers in psychiatric conditions
• Computational approaches for Parkinson's disease-related cognitive impairments

Guest Editors
Deepika Koundal, UPES Dehradun dkoundal@ddn.upes.ac.in
Amira S. Ashour, Tanta University, Egypt Amira.salah@f-eng.tanta.edu.eg
Yanhui Guo, University of Illinois, US yguo56@uis.edu
Mohit Mittal, Knowtion GmbH, Karlsruhe, Germany mohitmittal@ieee.org

Key Dates
Deadline for Submission: 30 May, 2025
First Reviews Due: 05 July, 2025
Revised Manuscript Due: 20 September 2025
Final Decision: 15 November, 2025

Special Issue on Contactless Human Sensing using Wireless Signals for Personalized Biomedical and Healthcare
Submission Date: 2025-05-31

Wireless sensing technology utilizes electromagnetic waves to perceive human individuals, providing accurate and
comprehensive human-related information for fields such as medical diagnosis and biological research. It offers new
possibilities for early disease diagnosis, treatment monitoring, and health assessment, addressing fundamental and
critical issues in biomedical and related fields. Meanwhile, with the gradual implementation of Integrated Sensing and
Communication (ISAC) in the fifth-generation-advanced (5G-A) and sixth-generation (6G) multi-functional networks,
using wireless signals, especially cellular signals, for contactless human sensing will become a general trend.
Furthermore, the radio communication division of the International Telecommunication Union (ITU-R) has recently
adopted ISAC among the key usage scenarios for IMT-2030/6G, making wireless human sensing technology more
indispensable in the coming 6G era. While current wireless human sensing has made significant strides, there is still
some way to go before its ubiquitous application and promotion. Some emerging applications for personalized
biomedical and healthcare, such as integrated wireless human sensing with telehealthcare, integrated communications
and wireless human sensing, as well as privacy and security issues in wireless human sensing, are also essential.
The main objective of this Special Issue is to address the unique challenges of wireless human sensing for personalized
biomedical and healthcare, and to bring contactless human sensing technique closer to reality. It will focus on various
theoretical and practical research on human sensing using wireless signals, aiming at bringing together researchers,
industry practitioners, and individuals working in related areas to share their new ideas, latest findings, and state-of-the-
art results. Ultimately, this special issue will provide a comprehensive tutorial of the state-of-the-art wireless human
sensing technologies for biomedical and healthcare.

Topics of interest include, but are not limited to, the following:
• Wireless human motion recognition approaches for personalized biomedical and healthcare
• Human imaging based on wireless signals for biomedical and healthcare
• Applications of artificial intelligence (AI) for wireless human sensing
• Human vital-sign (e.g., heartbeat and respiration) sensing for biomedical and healthcare
• Multi-source signal integration for contactless human sensing
• Human sensing datasets based on wireless signals for biomedical and healthcare
• Integrated wireless human sensing with telehealthcare
• Integrated communications and wireless human sensing for 6G
• Information security in personalized biomedical and healthcare based on wireless human sensing
• Experimental demonstrations and prototypes of wireless human sensing for personalized biomedical and healthcare

Guest Editors
Yuanhao Cui, Southern University of Science and Technology, cuiyuanhao@bupt.edu.cn
George C. Alexandropoulos, National and Kapodistrian University of Athens, alexandg@di.uoa.gr
Xinyu Li, Southeast University, xinyuli@seu.edu.cn
Jun Luo, Nanyang Technological University, junluo@ntu.edu.sg

Key Dates
Deadline for Submission: 31 May, 2025
First Reviews Due: 05 July, 2025
Revised Manuscript Due: 20 August, 2025
Final Decision: 31 September, 2025

Special Issue on Novel applications of Language Model Technologies in disease diagnosis
Submission Date: 2025-05-31

In recent years, the convergence of machine intelligence and healthcare has paved the way for significant advances in
disease diagnosis, particularly emphasizing the use of Language Model Technologies (LMTs). This special issue strives
to untangle the complications surrounding the use of LMTs in medical diagnostics, shedding light on the challenges
researchers and practitioners face in harnessing the full potential of these innovative tools. From deciphering intricate
medical data to enhancing diagnostic accuracy, LMTs present a myriad of opportunities that this issue seeks to explore
comprehensively. Additionally, the special edition emphasizes the imperative of fostering patient-centric healthcare
through the seamless integration of these technologies, ensuring that the diagnostic process becomes more efficient,
personalized, and empathetic. As we delve into the articles within this issue, we anticipate a profound understanding of
the current landscape, prospects, and the transformative impact that LMTs can have on revolutionizing disease diagnosis
and healthcare delivery.

However, integrating Language Model Technologies in smart diagnosis involves challenges. Working with unbalanced
data, feature engineering, data privacy concerns, and the interpretability of AI-driven diagnoses pose significant hurdles
that necessitate careful evaluation. This special focus seeks to address these intricacies. Opportunities abound in the
refinement of LMTs for tailored, patient-centric healthcare solutions, where the focus is not only on accurate diagnosis
but also on providing meaningful and understandable information to patients. The integration of LMTs promises to create
a more inclusive and empathetic healthcare ecosystem. As we navigate the technical intricacies of deploying LMTs in
smart diagnosis, it becomes imperative to strike a balance between innovation and ethical considerations to ensure that
the transformative potential of these technologies is harnessed responsibly for the betterment of patient outcomes and
overall healthcare delivery.

Topics of interest include, but are not limited to, the following:
• Novel applications of LMTs in disease diagnosis.
• Challenges and ethical considerations in deploying LMTs for medical purposes.
• Integration of LMTs with existing diagnostic tools and technologies.
• Patient-centric approaches in healthcare through LMT-enhanced diagnostics.
• Impact of LMTs on diagnostic accuracy and efficiency.
• Ensuring transparency in AI-driven diagnoses.
• Interdisciplinary perspectives on the convergence of healthcare and artificial intelligence.
• Ambient assisted living with LMTs for better livelihood.
• Harnessing wearable devices and real-time health data through LMTs.
• Case studies on the application of LMTs in smart diagnosis.

Guest Editors
Prof. Marcin Woźniak, Silesian University of Technology, Gliwice, Poland, marcin.wozniak@polsl.pl
Dr. Muhammad Fazal Ijaz, Melbourne Institute of Technology, Melbourne, Australia, mfazal@mit.edu.au
Dr. Mohit Mittal, Knowtion GmbH, Karlsruhe, Germany mohitmittal@ieee.org
Prof. Neal N. Xiong, Sul Ross State University, Alpine, USA, neal.xiong@sulross.edu

Key Dates
Deadline for Submission: 31 May, 2025
First Reviews Due: 05 July, 2025
Revised Manuscript Due: 05 August, 2025
Final Decision: 05 September, 2025