Part 3: Patient Recruitment
This new series focuses on how Machine Learning, Natural Language Processing, and Robotic Process Automation are changing the face of business. Each post contain a specific use case, the business value derived, and the technology synopsis to achieve the outcome.
Modern data and analytics techniques are improving patient recruitment in clinical trials through the use of data intelligence. This includes the identification of potential candidates, disease dispersion, and risk states. The analytics are driven from real world data sources, which use R programming and Shiny visualization with Hadoop as the underlying data store to drive the analysis. This means more patients are available for clinical trials, enabling better outcomes from the trials and less time and cost in finding the right patients.