Make More People Access
Excellent Medical Services
The contradiction between the requirements of big data integrity and the current situation of medical data fragmentation.
It is difficult to effectively exchange and share data globally.
Data ownership is complicated, and personal privacy is not effectively protected
Under the centralized management mode, problems of abusing personal privacy data and tampering with patient medical records or diagnostic records often arise.
The explosive growth of medical knowledge is difficult to share and flow effectively
Other medical practitioners can hardly participate in and integrate their knowledge to achieve systematic self-improvement of medical knowledge.
In order to meet the inquiries, screening, diagnosis, treatment and rehabilitation processes in medical care, LEBEN uses a middle-tier implementation that not only makes smart contracts compatible with more design languages, but also makes smart contracts interactive. It allows the calculated knowledge to be well expressed and more in line with the needs of the medical industry.
Based on cognitive computing, it constructs a mapping bridge from ontology cognition to digital world, implements the execution, communication, reasoning, decision making, planning, learning, reflection, supervision and other high-level behaviors of medical knowledge, and supports the self-evolution of medical knowledge thinking projection to make more high-value medical knowledge widely used.
Different medical data have different weights in privacy protection. According to the sensitivity and security requirements of medical data information, medical data is classified and gradated. Different levels of medical data are implemented by different cryptography to guarantee data exchange; at the same time, the data exchanged is available to use but is not invisible to the data consumer.
In order to complete the efficient and trusted exchange of decentralized data, computing power, and algorithm, LEBEN designs four kinds of super nodes in regard of data, computing power, algorithm and audit.