Identify Patterns & Detect Trends in Healthcare Data Sources
Healthcare Use Cases
One of the paradigm-shifting capabilities of deep learning is the ability to detect valuable patterns in large-scale, complex data sets, without the need for a priori rules. With Vyasa Cortex, deep learning pattern recognition technology can be applied to a wide range of quantitative and qualitative healthcare-related data. Cortex users can identify potential patient readmission events, cohorts for clinical trials and disease outcome probabilities.
Real World Evidence Analytics
It is becoming increasingly important to analyze real world evidence and 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 identify trends. Cortex provides exactly this type of tool. With the cutting-edge, AI-based approaches in Cortex, teams of end-users can continuously scan real world evidence sources and identify novel patterns.
Electronic Health Record (EHR) Mining & Structuring
End-users often need to be able to convert content in EHRs from unstructured formats into structured or semi-structured formats that contain concepts from the original sources. Vyasa 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.