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Characterizing Patients Across Hard-to-Diagnose Conditions in a Privacy-Preserving & Scalable Manner

Clinicians spend more than 35% of their time capturing patient data, symptoms, family histories, lab results and such key information in the form of digitized patient records. In spite of this, more than 60% of patients with rare and hard-to-diagnose conditions are not diagnosed in a timely manner. This is due to lack of scalable and speedy access to actionable intelligence from such records, which is required by clinicians to map patient journeys.

This short Q&A style blog discusses how Pangaea’s AI-driven product, PIES (Pangaea’s Intelligence Extraction and Summarization), is improving patient outcomes through characterization of patients and mapping their journey across hard-to-diagnose conditions by discovering clinically actionable intelligence from their records in a scalable, evolving and privacy-preserving manner. This has proven to be critical for finding more miscoded, misdiagnosed, undiagnosed and at-risk patients in the context of precision medicine, preventative health and clinical trials.

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