Case Study: Healthcare
Insights from Medical documents for effective Healthcare
A national healthcare payer was using a non-scalable and inefficient business model to determine risk conditions by manually reading scanned physician and hospital multi-page notes.
- xpresso.ai is being used to augment the manual workflow with automation that outputs relevant pages to read (manually) instead of the whole document.
- Computer Vision is utilized to read the scanned notes and convert them into machine readable text.
- The text is then pre-processed to correct spelling errors.
- Deep Learning models categorize the text into disease, procedure and drug using a medical ontology.
- The final output is provided in standard JSON format.
- The solution is enabling the client to increase notes analysis efficiently by 42%.
- This is helping them scale up without increasing number of employees.