Ways In Which Blockchain And AI Innovate The Medical Industry
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Ways In Which Blockchain And AI Innovate The Medical Industry

Monday, August 3, 2020 7:45 AM
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NEW YORK, NY / ACCESSWIRE / August 3, 2020 / During the pandemic, the value of health and medical big data has become increasingly prominent, and the capabilities of medical big data are much more than that. It can be widely used in clinical medicine, health management, public health emergency, epidemic prevention, and other industrial fields. At the same time, with the rapid development of science and technology, the empowerment of big data in the medical industry has become a global medical development trend.

"A global blockchain in the healthcare market is expected grow at a CAGR of 63.85% from 2018 to 2025, to reach a value of $5.61 billion by 2025. The use of blockchain for healthcare data exchange will contribute the largest market share throughout the forecast period, reaching a value of $1.89 billion by 2025, owing to the use of blockchain to solve the most widespread problem in healthcare information systems related to interoperability and non-standardization that has created data silos in the industry."

BIS Research Report 2018

Difficulties in big medical data: CyberVein breaks data barriers

The value of medical big data is becoming more and more prominent, but its natural sensitivity and particularity have hindered its full use of value in information construction. In this regard, CyberVein cracked the application problem of medical big data from a technical point of view, building a medical data center that integrates transaction processing and analysis.

CyberVein's medical data center provides an one-stop solution for medical big data applications through five core technologies of data connection, storage, management, analytics, and use, and four aspects: data collection layer, data source layer, big data center and application market.

1) CyberVein data can be accessed-data collection layer: diversified data collection capabilities

At this stage, medical big data is becoming more abundant, including but not limited to patient diagnosis and treatment data in hospitals, medical-related department data, health data in the real environment, Internet data, data from third-party medical consulting institutions, and so on.

In the face of massive amounts of data, most medical institutions use manual entry for data collection. This method is costly, low in efficiency, and has a high risk of data loss. In addition, the standards and interface specifications of different institutions and different systems are different, which makes it very difficult to collect and integrate the underlying data.

"Matching the correct individual to his or her health data is critical to their medical care. Statistics show that up to one in five patient records are not accurately matched even within the same health care system. As many as half of the patient records are mismatched when data is transferred between healthcare systems."

Shaun Grannis, Director of Center for Biomedical Informatics

CyberVein solution: The data collection layer of CyberVein medical data center has database backup and recovery, integrated platform, materialized view, data synchronization tools (such as OGG), and multiple data collection and access technologies (including ETL, crawlers, etc.), which fundamentally solve the traditional problem of weak medical data collection capabilities.

In addition, CyberVein medical data center provides a reasonable selection of data collection solutions based on different construction units, and finally realizes the analysis, collection and sharing of multi-source heterogeneous data such as internal data of medical institutions, medical-related department data, health data and Internet data.

2) Data storage and management - data source layer, big data center: laying the foundation for medical data circulation and sharing

various unstructured data continue to emerge, and the existing medical information system cannot meet the storage requirements of big data in terms of storage space, storage speed, and storage structure. A lot of data has to be abandoned, resulting in the loss of valuable medical data.

CyberVein solution: CyberVein data center has integrated DAG-based distributed storage, which supports asynchronous verification and parallel processing of each node. The more nodes, the faster the speed and the better the scalability, which can solve the problem of expansion and efficiency.

At the same time, the data is processed, such as the unified processing of the necessary fields, to achieve data standardization, to build a unified data asset system, and to improve the efficiency of data coordination and reuse.

Through the establishment of an access control model, identity authentication technology is used to manage and control component operation permissions. That is, it meets the needs of medical data sharing between different hospitals and guarantees patient data privacy and medical staff's access to data.

Data Processing Diagram

Data format conversion for single row and single field granularity. Hospital data comes from multiple systems, and the data format of the same system varies from hospital to hospital, and there are various abnormal data formats in the hospital's original system data. In order to unify the processing, the necessary fields need to be standardized when data is processed.

Disease Synonym Map

Due to the irregularity and randomness of clinical data, it is necessary to standardize clinical master data before using medical big data. Master data: the dictionary library in the clinical system, such as: department dictionary, diagnosis dictionary, medicine dictionary, inspection dictionary, etc. Reference specifications are: ICD10, ICD11, MESH (medical subject word list), ICD-9-CM-3, LOINC, CFDA, ATC classification.

3) Data analytics and use - application market: realize the value of data and promote the development of the medical industry

The application of medical big data in clinical scientific research is weak. On one hand, it is because traditional manual data entry and statistical software combined with data analysis methods have limited capabilities for data relevance research and prediction research, which severely restricts the value of medical big data. On the other hand, in the development of data analysis models and tools, ordinary medical institutions have the problem of insufficient talents. As a result, a large amount of medical data has not exerted its clinical scientific research value and its application ability is weak.

"There's a very complex ecosystem that exists in healthcare, and you've got competition where you really need transparency, where data is thought of as currency, and you've got a lot of cybersecurity issues… When you start to see that ecosystem come together and establish the rules of the game, that's where this is going to change."

Barb Hayes, General Manager at IBM Watson Health

CyberVein solution: CyberVein data center is based on data, and uses the computing power platform to achieve distributed and parallel execution of computing tasks, improve the computing efficiency of massive multi-source heterogeneous data, quickly confirm the data relationship and perform federated learning, and achieve data visualization under the premise of ensuring data privacy. Through interactive visualization interface, to achieve comprehensive display of medical and health big data.

Finally, various medical big data platform basic applications will be built. Including but not limited to: clinical data search, patient panoramic diagnosis and treatment view, patient data services, clinical research applications, clinical knowledge base, department operations, clinical assistance decisions, etc.

Patient Holographic View

Based on the clinical application of clinical data, clinicians can consult the patient's medical information through a clear and friendly unified view, thereby optimizing the doctor's operation process, so that the clinician can have an overall understanding of the patient's medical situation in a short time.

"Patient holographic view" is the most basic application in clinical scenarios. Big data applications can give patients a more friendly diagnosis and treatment support experience with holographic views, collect full clinical data content, and realize the simultaneous viewing of clinical EMR data and examination reports.

Intelligent Recognition of Keratitis Images

Based on CyberVein's computing power platform and federated learning platform, artificial intelligence is empowered, which can not only simulate the patient's condition, but also accurately diagnose the patient's reactions and problems during the treatment process, which promotes intelligent medical development and has made important contributions to human health.

CyberVein's keratitis image intelligent recognition system has been tested by 521 doctors in the Sir Run Run Shaw Hospital of Zhejiang University. Through federal learning, the diagnostic accuracy rate of keratitis exceeded 85%, which surpassed 96% of the doctors. Also, the medical research data backup is realized on the DAG storage chain.

CyberVein to promote the rapid development of value-oriented medical system

The establishment of CyberVein's medical data center is planned from the four aspects of data source layer, data collection layer, big data center, and application market, integrating artificial intelligence analysis technology, from improving the basic level of data quality to flexible use of multiple statistical analysis tool to improve the quality of scientific research results and solve the current problem of insufficient medical data processing capabilities.

At the same time, the establishment of the CyberVein medical data center will also promote the perfect development of the value-oriented medical system. The value-oriented medical system is the trend of global medical system transformation. In recent years, global medical and health expenditures have generally grown rapidly at an unsustainable rate. Controlling medical costs has always been considered a problem for global medical policy makers, payers, and medical service institutions.

Therefore, in the context of controlling medical costs on a global scale and seeking the best curative effect, the establishment of CyberVein's medical data center will help the medical industry to rely on transparent and high-quality data, analyzing data differences to form benchmarks, and determining the current best clinical practice and behaviour, and finally realize medical value through continuous feedback and learning, prompting the acceleration of the era of value-oriented medical system.

Media Contact

CyberVein Customer Support
Rachel Yu
[email protected]

SOURCE: CyberVein

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