Integration of Artificial Intelligence, Blockchain, and Wearable Technology for Chronic Disease Management: A New Paradigm in Smart Healthcare
Open accessAbstract
Chronic diseases are a growing concern worldwide, with nearly 25% of adults suffering from one or more chronic health conditions, thus placing a heavy burden on individuals, families, and healthcare systems. With the advent of the "Smart Healthcare" era, a series of cutting-edge technologies has brought new experiences to the management of chronic diseases. Among them, smart wearable technology not only helps people pursue a healthier lifestyle but also provides a continuous flow of healthcare data for disease diagnosis and treatment by actively recording physiological parameters and tracking the metabolic state. However, how to organize and analyze the data to achieve the ultimate goal of improving chronic disease management, in terms of quality of life, patient outcomes, and privacy protection, is an urgent issue that needs to be addressed. Artificial intelligence (AI) can provide intelligent suggestions by analyzing a patient's physiological data from wearable devices for the diagnosis and treatment of diseases. In addition, blockchain can improve healthcare services by authorizing decentralized data sharing, protecting the privacy of users, providing data empowerment, and ensuring the reliability of data management. Integrating AI, blockchain, and wearable technology could optimize the existing chronic disease management models, with a shift from a hospital-centered model to a patient-centered one. In this paper, we conceptually demonstrate a patient-centric technical framework based on AI, blockchain, and wearable technology and further explore the application of these integrated technologies in chronic disease management. Finally, the shortcomings of this new paradigm and future research directions are also discussed.
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Generative AI models are designed to predict and generate new information, offering unique insights into disease progression and complication risks, unlike traditional AI models focused on classification and regression.
“Unlike traditional AI models that are focused on classification and regression tasks, some studies mentioned that generative models are designed to predict and generate new information, offering unique insights into disease progression and complication risks (44,45).”
From Generative artificial intelligence in predictive analysis of diabetes and its complications: a narrative review (2025) · cites this paper as [45]
The opening overview (section and page not supplied) describes AI analyzing wearable-device data to inform diagnosis and treatment, but does not discuss generative models. Searches for generative models, classification and regression, disease progression, and complication risks found no passage in our copy supporting the claimed comparison. (LLM, conf=0.75)
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Hamine, S., Gerth-Guyette, E., Faulx, D., Green, B. B., & Ginsburg, A. S. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.3951 · Cited by 1,149 · cited 2× · see citing works
“In the management of chronic diseases, wearable devices can be worn directly on the body in the form of portable medical electronic equipment for sensing, recording, analyzing, regulating, and intervening to keep the person wearing the device healthy [4, 5] .”
BackgroundMobile and Wearable Technology for the Monitoring of Diabetes-Related Parameters: Systematic Review
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The emergence of AI-based wearable sensors for digital health technology: a review
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- Authors
- Xie, Y., Lu, L., Gao, F., He, S.-J., Zhao, H.-J., Fang, Y., Yang, J.-M., An, Y., Ye, Z.-W., & Dong, Z.
- Affiliations
- Wuhan Union Hospital (CN)
- Wuhan Puai Hospital (CN)
- Huazhong University of Science and Technology (CN)
- Corresponding author
- Dong, Zhe
- Venue
- Current Medical Science
- Published
- 2021-12
- Volume
- 41
- Issue
- 6
- Pages
- 1123-1133
- ISSN
- 2096-5230 (ISSN-L)
- 2523-899X
- PMC
- PMC8702375
- OpenAlex
- W4200534512
- Cited by
- 234
- References
- 3
- Citations by year
- 2026: 39 · 2025: 90 · 2024: 58 · 2023: 37 · 2022: 10
- FWCI
- 23.74
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Current Medical Science (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (81974355, 82172525)
- Topics
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- chronic disease management, wearable devices, artificial intelligence, blockchain, smart healthcare, patient-centered care, decentralized data sharing, healthcare data privacy, physiological data analysis, patient-centered care model
- MeSH terms
- Wearable Electronic Devices, Blockchain, Artificial Intelligence, Chronic Disease, Delivery of Health Care, Humans, Disease Management, Inventions
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