AI/ML in RF and Microwave Sensors for Medicine and Biomedical Applications
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".
Deadline for manuscript submissions: 30 June 2026 | Viewed by 1627
Special Issue Editors
Interests: bioinformatics; deep learning; machine learning; biomedical image processing
Special Issues, Collections and Topics in MDPI journals
2. Department of Computer Science and Computer Engineering, University of Wisconsin-La Crosse, La Crosse, WI 54601, USA
Interests: transformation optics/electromagnetics (TO/TE) and its applications for next-generation sensors and devices; engineered electromagnetic materials; RF/microwave devices for IoT and healthcare; machine learning for wireless communications and biomedical applications; 3D-printed flexible and wearable electronics for embedded systems and biomedical applications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent advancements in RF and microwave devices have significantly enhanced their utility in medicine and biomedical applications, revolutionizing areas such as diagnostics, therapeutic systems, and medical imaging. With the growing integration of artificial intelligence (AI), deep learning, reinforcement learning, and emerging technologies like explainable AI and federated learning, there is a tremendous opportunity to drive innovation and tackle challenges in this interdisciplinary domain.
This Special Issue aims to compile original research and review articles focusing on cutting-edge developments, solutions, and applications of RF and microwave technologies in medicine, emphasizing the transformative role of AI-powered methodologies.
We encourage submissions exploring theoretical innovations, experimental validations, and interdisciplinary approaches combining RF technologies with advanced AI techniques. By addressing these topics, this Special Issue aims to highlight the latest advancements and foster collaboration across fields to improve medical outcomes and patient care.
Dr. Rahul Gomes
Dr. Dipankar Mitra
Guest Editors
Manuscript Submission Information
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Keywords
- AI-driven advancements in RF and microwave medical imaging
- microwave-based non-invasive diagnostics and therapeutic systems
- explainable AI for RF and microwave healthcare applications
- federated learning for distributed medical data analysis using RF systems
- deep learning in microwave hyperthermia and ablation therapies
- integration of RF devices with biomedical sensors for real-time monitoring
- reinforcement learning in adaptive RF-based treatment protocols
- RF and microwave devices for wearable and implantable medical systems
- AI-powered microwave imaging for tumor detection and monitoring
- RF-based solutions for point-of-care diagnostics
- challenges and solutions in the standardization and safety of RF devices in medicine
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