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Using Spark NLP to Enable Real-World Evidence (RWE) and Clinical Decision Support in Oncology

EHRs collect mass amounts of critical patient information but across the healthcare industry, most lack the ability to take meaningful action with this data and put it to its best possible use. RWE can make a difference by helping to determine the best course of treatment, particularly in the complicated field of cancer care.

Spark NLP Healthcare modules are specifically designed to unlock this potential of RWE data by applying state-of-the-art clinical NLP algorithms in a secure platform and accurately extract facts from free-text medical reports, which can then be used for a variety of applications like cohort selection, real-world evidence studies, clinical trial recruitment, and others. In this demo, we will demonstrate how we leveraged Spark NLP to analyze longitudinal records of cancer patients, enabling oncologists to see patient data clearly and saving thousands of hours for human-level abstraction.

Hardening a Cleanroom AI Platform to allow model training & inference on Protected Health Information

Artificial intelligence projects in high-compliance industries, like healthcare and life science, often require processing Protected Health Information (PHI). This may happen because...