Author:
Dean Rakic
Affiliation:
Enterprise Application Development (EAD), Germany
Keyword(s):
Blockchain, IoT, Interoperability, Patient Record, E-Health, Evidence-based, Predictive Analytics.
Related
Ontology
Subjects/Areas/Topics:
Ambient Intelligence
;
Artificial Intelligence
;
Business Analytics
;
Cardiovascular Technologies
;
Computing and Telecommunications in Cardiology
;
Data Engineering
;
Decision Support Systems
;
Decision Support Systems, Remote Data Analysis
;
Health Engineering and Technology Applications
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Software Development
;
Symbolic Systems
Abstract:
A big portion of data that are produced by various digital ecosystems has met a lack of interoperability on
the line between applications, data streams and predictability in the healthcare. The new technology
approach in the distributed messaging and Blockchain became a key component of many healthcare
technology stacks and can derive real-time data streams as valuable and scalable enough to enable real-time
healthcare predictive analytics. Besides, ingesting data streams from various sources from patterns of data
can extend healthcare trend analysis to the higher level of prediction, accuracy and improve models that
suffer from complex and long-running analyses. A better response, lower availability requirements and
unifying predictive modelling will accelerate healthcare interoperability and thus increase the accuracy of
diagnoses, put the evidence-based medicine (EBM) in the right direction and other healthcare benefits
which increase optimum outcomes and quality.