How can NLP text mining help improve clinical risk monitoring and hospital efficiency?

Some of the most valuable data for identifying patient risk, is often locked away in unstructured patient data, limiting its use. For example, social deterimants provide important insights into population risk and incidental factors such as a mention of a pulmonary nodule in a radiology report can give an early warning of lung cancer. Natural Language Processing (NLP) can unlock, understand and structure this data, and transform it into real patient insight.

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