Derive Valuable Insights & Identify Patterns in Healthcare Data Sources
Concept Recognition Based EHR Annotation
A.I. Based Novel Concept Term Recognition
Deep Learning Based Predictive Analytics Modules
One of the paradigm shifting capabilities of deep learning technologies is that valuable patterns can be detected in large-scale, complex data sets without the need for a priori rule sets. Deep learning pattern recognition technology can be applied in Vyasa Cortex to a wide range of quantitative and qualitative healthcare related data. With Cortex, users can identify potential patient re-admission events, cohorts for clinical trials and disease outcome probabilities.
Real World Evidence Analytics
With greater and greater emphasis on the analysis of real world evidence to monitor patterns relevant to healthcare outcomes, tools are needed to consume content from a wide range of data sources, easily integrate that content and apply advanced analytics to derive and identify patterns. Vyasa Cortex provides exactly this type of tool. Teams of end-users can use Cortex to continuously scan real world evidence data streams and sources to identify novel patterns and trends using cutting-edge AI based approaches.
Electronic Health Record (EHR) Mining & Structuring
Often end-users need to be able to convert content in EHR records from unstructured formats into a structured or semi-structured format centered on the concepts embedded in the originating sources. Vyasa Cortex’s Neural Concept Recognition technology can be trained to identify concepts in messy data sources and convert these concepts into structured forms for easier and more organized analysis.