Application of Deep Learning and Blockchain in Healthcare Systems
A special issue of Healthcare (ISSN 2227-9032). This special issue belongs to the section "Artificial Intelligence in Medicine".
Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 5105
Special Issue Editors
Interests: food AI; dietary assessment; deep learning for healthcare applications; food recommendation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the development of the Internet of Things (IoT) and artificial intelligence (AI), the healthcare field has been gradually digitized. In the current digital era, AI-driven healthcare systems have become a popular direction to pursue. Deep learning/ machine learning has been proven to be useful in all areas of healthcare applications, including but not limited to disease diagnosis, healthcare monitoring, patient identification, treatment recommendation, dietary assessment, privacy protection and other specialized healthcare support in image analysis. For example, AI-driven healthcare systems can provide semi/fully-automated diagnostic services to assist doctors in making decisions and developing solutions. Moreover, AI techniques can also be utilized to assist the operation of surgery, such as through manipulation, navigation, etc. With the combination of IoT and AI technology, wearable medical devices/sensors can further facilitate the long-term monitoring of a patient’s health conditions, which reduces the burden of practitioners and improves the efficacy of treatment.
In recent years, with the advances in blockchain technology, new scopes of applications have been discovered, especially in the field of Fintech. However, applications in healthcare have not yet been extensively studied. The unique advantages of blockchain, such as decentralized architecture, immutable nature, public visibility, data storage, etc., have great potential to assist healthcare systems. Therefore, it is generally believed that blockchain technology may also provide a direct contribution to the next generation of healthcare systems.
Dr. Frank Po Wen Lo
Dr. Bo Xiao
Guest Editors
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Keywords
- healthcare monitoring systems
- artificial intelligence for healthcare applications
- deep learning for smart health
- blockchain technology for healthcare applications
- metaverse-based healthcare monitoring systems
- disease diagnosis
- privacy protection of patient data
- data security
- innovative IoMT solutions
- AI-driven wearable sensors
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