Call for papers - AI in telemedicine

Guest Editors

Hassan Ghasemzadeh, PhD, Arizona State University, USA
Vijay Bhaskar Semwal, PhD, Maulana Azad National Institute of Technology Bhopal, India

Submission Status: Open | Submission Deadline: 14 November 2025

BMC Artificial Intelligence is calling for submissions to our Collection on AI in telemedicine. This Collection invites researchers to contribute studies on the role of artificial intelligence in telemedicine. We welcome submissions that explore various aspects of AI, including machine learning, deep learning, and their applications in remote monitoring and telehealth. The goal is to advance our understanding of how AI can enhance healthcare delivery and improve patient outcomes in a virtual setting.

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Meet the Guest Editors

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Hassan Ghasemzadeh, PhD, Arizona State University, USA

Hassan Ghasemzadeh is a Program Director and an Associate Professor in the College of Health Solutions at Arizona State University (ASU). He is on the graduate faculty of the biomedical informatics and data science, computer science, computer engineering, and biomedical engineering programs at ASU. Prior to joining ASU, he was an assistant/associate professor of computer science at Washington State University (WSU 2014-2021) and a postdoctoral research manager at the University of California Los Angeles (UCLA 2011-2013). Dr Ghasemzadeh's research interests include digital health, machine learning, mobile health, and algorithm design.

Vijay Bhaskar Semwal, PhD, Maulana Azad National Institute of Technology Bhopal, India

Dr Vijay Bhaskar Semwal is an Assistant Professor in the Department of Computer Science and Engineering at Maulana Azad National Institute of Technology (MANIT Bhopal). Dr Semwal's research interests encompass a variety of fields, including human-robot interaction, IoT, wearable sensor-based health monitoring systems, bipedal robotics, gait analysis and synthesis, artificial intelligence, machine learning algorithms, and theoretical computer science. In addition to his research, Dr Semwal has organized and conducted more than ten Short-Term Training Programs (STTPs) and workshops, as well as three international conferences. He is a senior member of several professional organizations, including IEEE, the International Association of Engineers (IAENG), the Indian Academy of Neurosciences (IAN), and the Soft Computing Research Society (SCRS).

About the Collection

BMC Artificial Intelligence is calling for submissions to our Collection on AI in telemedicine.

The integration of artificial intelligence (AI) in telemedicine represents a transformative shift in healthcare delivery, enhancing the way medical services are provided remotely. Telemedicine encompasses a wide range of practices, including virtual consultations, remote monitoring, and the use of advanced algorithms to analyze patient data. AI technologies such as machine learning and deep learning are increasingly being used to improve diagnostic accuracy, personalize treatment plans, and streamline workflows; the aim is to automate workflows to deliver the best possible patient experience.

The significance of AI in telemedicine is underscored by the rapid advancements in technology and the growing demand for accessible healthcare solutions. The COVID-19 pandemic has led to a rapid increase in the use of telehealth, leading to developments in AI applications that address the need for remote patient management and monitoring. These advancements not only help to overcome geographical barriers to healthcare access but also enable more efficient resource allocation and improved patient engagement, paving the way for a more responsive healthcare system.

As research continues in this field, we can anticipate breakthroughs in AI-driven telemedicine solutions that further improve clinical decision-making and the patient experience. Future developments may include more sophisticated AI algorithms capable of predicting patient needs and outcomes, as well as improvements in interoperability between various telehealth platforms. Additionally, there is the potential for AI to play a crucial role in developing personalized healthcare strategies, tailored to individual patient profiles, thereby maximizing the effectiveness of telemedicine. Moreover, AI-driven remote monitoring systems create unique opportunities for disease prevention by providing individuals with continuous health assessments and proactive health solutions. We invite contributions that examine a wide range of topics relating to the application of AI in telemedicine and telehealth, including but not limited to:

AI applications in remote patient monitoring
Machine learning techniques in telehealth
Digital health for disease diagnosis, prevention, and management
Deep learning for diagnostic imaging in telemedicine
Virtual health consultations and patient engagement strategies
AI-powered wearable and mHealth systems
Ethical considerations in AI-driven telemedicine

All manuscripts submitted to this journal, including those submitted to collections and special issues, are assessed in line with our editorial policies and the journal’s peer review process. Reviewers and editors are required to declare competing interests and can be excluded from the peer review process if a competing interest exists.

Please email Alison Cuff, the editor for BMC Artificial Intelligence, (alison.cuff@biomedcentral.com) if you would like more information before you submit.

There are currently no articles in this collection.

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 "AI in telemedicine" from the dropdown menu.

All manuscripts submitted to this journal, including those submitted to collections and special issues, are assessed in line with our editorial policies and the journal’s peer review process. Reviewers and editors are required to declare competing interests and can be excluded from the peer review process if a competing interest exists.