In the era of Electronic Health Records, it’s possible to examine the decision outcomes made by doctors and identify patterns of care by generating evidence from the collective experience of patients.
In this webinar, Stanford Assistant Professor Nigam Shah will show you methods that transform unstructured patient notes into a de-identified, temporally ordered, patient-feature matrix. Four use-cases will be examined, which use the resulting de-identified data matrix to illustrate the learning of practice-based evidence from unstructured data in electronic medical records.
This webinar will teach you the practical value of:
- Monitoring for adverse drug events
- Identifying drug-drug interactions
- Profiling the safety of off-label drug usage
- Generating practice-based evidence for difficult-to-test clinical hypotheses.
