Medical big data holds tremendous promise to transform the medical industry but is currently facing big challenges. The abundant medical data amassed from various sources is extremely diverse in type, format, and context. As a result, traditional databases are not able to handle medical big data efficiently. At the moment storing, recording, and sharing medical data securely among diverse systems and applications is a costly and tedious affair.
According to the statistics, less than 10% of the health care organizations share their medical data with any other party. Thus most of the medical data is lying in silos. This is happening because existing systems lack interoperability. Hence transmitting, retrieving, cleaning, and analyzing medical data is an enormously challenging task. CyberVein aims to address all these challenges with a one-stop solution.
In short, medical big data requires an intelligent and highly secure data center. CyberVein seems to have cracked the code. It has amalgamated the capabilities of blockchain and artificial intelligence technology into its one-stop medical data center. The CyberVein medical data center is capable of:
Here is how CyberVein medical data center addresses these challenges:
Problem 1: Diverse sources of medical data
The sources of medical data are largely diverse. The medical data pours in from government agencies, patient portals, research studies, generic databases, Electronic Health Records, public records, search engine data, smartphones, payer records, and many more sources.
Effectively, it is very difficult and costly to integrate the data coming in from so many sources. Moreover, at some data points, manual maintenance of patient records leads to errors or some kind of data loss.
The CyberVein medical data center offers its users a powerful data collection layer. The layer utilizes tools like Oracle Golden Gate (OGG) to synchronize data between heterogeneous environments. Furthermore, it uses ETL tools that easily unite multiple data sources. Apart from that the data center offers backup and recovery provision, materialized views, and more.
Effectively, these tools make analysis, collection, and sharing of the highly diverse medical data possible.
Problem 2: 3 Vs challenge of medical big data
The velocity, variety, and volume of data produced in the medical industry is rapidly changing. Thus it is becoming extremely challenging for IT infrastructure providers to build a model that scales as per the flow of medical information. As a result, the existing systems abandon data and lets the value disappear.
At times the data is time critical and is useful only when it flows in with minimum delay. Even when the traditional system is efficient, it struggles to maintain the speed of data transfer when the in-flow of data is very high.
In the data storage and management layer, CyberVein utilizes DAG (Directed Acyclic Graph). By using DAG for parallel processing of transactions, CyberVein medical data center solves the scalability issues. In theory, a DAG is capable of delivering a throughput of millions of transactions per second.
This layer is also made capable of data standardization. It achieves this by identifying necessary fields and then unifies their processing. This makes data reusable also. CyberVein medical data center also promises user privacy protection and data security (blockchain). The medical data is kept local and the application can exchange data only on a parameter basis. Smart contracts define these parameters. Thus the data privacy issue is also addressed.
Previously, we interviewed Jack Ge, Managing Director CyberVein on the Altcoin Buzz YouTube channel.
Problem 3: Value of data for clinical scientific research is suffering
Large amounts of medical data hold lots of value for clinical scientific research. But the data must first be collected, transmitted, cleaned, and then used. Currently, some of the data is being collected manually, it is then transmitted over slow channels and is then fed to data analysis tools. The process is slow, inefficient, and leads to data losses. Furthermore, the data analysis tools have limited capabilities. The end-user is not able to derive relevant data from these tools.
As a result, the data collected and analyzed is not of much value for scientific research.
CyberVein medical data center is a powerful computational tool as it utilizes DAG. This improves the data processing efficiency of the system. On top of that it utilizes federated learning(AI) that ensures every user of the platform can derive precise value out of the data. It also makes the system capable of self-learning. Such a set-up allows anyone an opportunity to build a database, smart contract, and DApp to access the database on a parameter basis. The platform users can create their own data ownership rights and data transaction formats. With federated learning, they can also build precise data value conversion capabilities.
Effectively, the CyberVein medical data center can also be used to provide a patient’s medical history holographic view. It can also provide a combined friendly diagnosis by combining the EMR data and examination reports. All this can help health care professionals in quick diagnosis.
A Real-world tested platform
CyberVein’s built a keratitis image intelligent recognition system for Sir Run Run Shaw Hospital of Zhejiang University. Over 500 doctors tested the system and recorded a diagnostic accuracy rate of 85%.
Not only will this transformation control the costs of medical care, it will also help improve the quality of scientific research. Thus CyberVein promises to help build a value-oriented medical system.
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