AI-Enabled Sensing Technology for Smart Healthcare and Precision Diagnosis
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: 25 June 2026 | Viewed by 31
Special Issue Editor
Interests: machine learning/deep learning for health data analytics; health informatics; explainable AI epidemiology; population health; big data analytics; data linkage (of electronic health records); information aggregation/integration data mining and knowledge discovery; data mining and knowledge discovery
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue explores the transformative role of artificial intelligence in reshaping modern healthcare through intelligent sensing technologies. As AI algorithms grow increasingly sophisticated and sensor technologies become more advanced, their integration is enabling faster, more accurate, and highly personalized diagnostics and treatment strategies.
We welcome original research and practical applications demonstrating how AI-powered sensing systems are advancing clinical decision-making, real-time patient monitoring, and early disease detection. Emphasis is placed on interdisciplinary approaches that combine wearable devices, medical sensors, machine learning models, and edge/cloud computing to support data-driven healthcare innovation.
Submissions addressing the integration of edge computing, cloud-based analytics, and next-generation wireless networks to improve diagnostic accuracy and healthcare delivery are particularly encouraged. We welcome contributions from academia and industry that drive innovation in smart, data-driven healthcare.
Dr. Muhammad Azizur Rahman
Guest Editor
Manuscript Submission Information
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Keywords
- AI-driven real-time health monitoring
- data fusion from wearable/medical sensors
- secure data transmission in healthcare IoT
- ML/DL-based diagnostic models
- federated and privacy-preserving AI
- predictive analytics for early detection
- digital twins and virtual patient models
- explainable AI for clinical decision support
- 5G/6G-enabled remote diagnostics
- energy-efficient AI for continuous monitoring
- multimodal data analysis (e.g., imaging, genomics)
- adaptive systems for personalized care
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