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Accelerating clinical risk adjustment through Natural Language Processing

Healthcare systems are increasingly looking to natural language processing (NLP) technology to maximize their performance of risk arrangements and enhance their value-based care program.

The number of Healthcare systems that have adopted a form of NLP technology has increased significantly in recent years, leading to improved accuracy and completeness of risk capture.

This session will highlight the challenges of risk adjustment and demonstrate the results achieved by leveraging Spark NLP for Healthcare to accelerate the review and extraction of diagnosis codes from unstructured clinical notes.

We will show an end-to-end platform architecture that incorporates state-of-the-art NLP models to understand and extract relevant data accurately and reliably from pages of long unstructured medical records, drastically reducing the time required compared to a manual effort.

Deep6 accelerates clinical trial recruitment with Spark NLP

Recruiting patients for clinical trials is a major challenge in drug development. Finding patients requires an in-depth understanding of their medical histories and...