Deep Learning for Sensor-Driven Medical Applications
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".
Deadline for manuscript submissions: closed (28 August 2023) | Viewed by 5776
Special Issue Editors
Interests: deep learning; medical image analysis; healthcare applications; secret sharing scheme & digital image security
Special Issues, Collections and Topics in MDPI journals
Interests: AI; machine learning; medical image processing
Special Issues, Collections and Topics in MDPI journals
Interests: MAC; routing protocols for next-generation wireless networks; wireless sensor networks; cognitive radio networks; RFID systems; IoT; smart city; deep learning; digital convergence
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent advances in sensing technologies have enabled the healthcare sector to improve the quality of its services. Furthermore, the design of small and lightweight smart sensors has enabled systems to act as a vital part of advanced developments in unobtrusive and unsupervised approaches to home-rehabilitation and the continuous monitoring of patients’ health status. In the present healthcare system, the application of deep learning (DL) is widespread to accomplish enhanced quality of service in disease diagnosis, acute disease detection, image analysis, drug discovery, drug delivery, and smart health monitoring. This Special Issue on “Deep learning for Sensor-Driven Medical Applications” focuses on new sensing technologies, measurement techniques, and their applications in medicine and healthcare. We offered this topic, being aware of the fundamental role that smart sensors can have in enhancing the quality of healthcare services in both acute and chronic conditions as well as for prevention towards a healthy life and active aging. This Special Issue welcomes both original research papers and review articles focusing on innovative ideas. Topics of interest include, but are not limited to:
- Sensor-enabled medical data for disease diagnosis and monitoring;
- Computer aided diagnosis models;
- Wearables and Telemedicine;
- Data Security and Privacy Mechanisms in sensor enabled healthcare system;
- Deep learning for medical data;
- Computational intelligence for medical data;
- Big data analytics for healthcare applications;
- Sensors and Systems for Brain Computer Interfaces.
Dr. Shankar Kathiresan
Prof. Dr. Seifedine Kadry
Dr. Gyanendra Prasad Joshi
Guest Editors
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