Mining data from clinically registered electronic medical records appears to be an ideal task for plugging in artificial intelligence (AI) technology—automating data mining and freeing up clinically important resources. However, simply replacing human data extractors with AI results in lower-than-expected accuracy and limited confidence in the results. Maybe it’s time to rethink this approach and instead take advantage of the strengths and limitations of technology and human abstractions.
This webinar discusses how human-machine teams can leverage human clinical expertise and complex problem-solving capabilities to tackle more challenging areas of clinical registries, as well as the speed and accuracy of AI techniques in more immediate areas. The result is more accurate and timely data for clinical registries and internal patient care programs.
join us July 20 at 2pm ET In this webinar we will discuss:
- The strengths and limitations of artificial intelligence
- Why a Human-Machine+Computer Data Mining Approach Produces the Best Results
- How artificial intelligence approaches such as machine learning and natural language processing can standardize clinical registry data
- How to provide clinical registry data in real-time for patient care, quality programs, and other internal programs in hospital systems
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