Precision medicine and population health initiatives are driving demand for more data, more quickly, to support improved clinical research and outcomes. With much of cancer data trapped in pathology and radiology reports there is significant interest in how these unstructured textual data can be turned into actionable insights. Such data is vital for use in tumor boards, cancer registries, biobanks and data warehouses for population health.
In this webinar Linguamatics will share its extensive experience using Natural Language Processing (NLP) to extract valuable information from pathology reports, and will demonstrate their Pathology NLP application with pre-built, configurable queries that support rapid implementation and organizational value. Central to this new version is an Oncology ICD-O coding component that extracts histology grade and behavior and body site information from patient notes. We will demonstrate the software using pathology reports from The Cancer Genome Atlas (TCGA) project.
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