Abstract
Quality monitoring is of increasing importance in procedural fields, especially for colonoscopy. Adenoma detection rate (ADR) predicts the risk for developing colorectal cancer (CRC) following a negative screening colonoscopy, however, finding the ADR using automation is challenging because it is tied to text reports and is not easily accessible without manual review. Natural language processing (NLP) has been used to obtain ADR, although with significant customized effort, cost, and has been limited to single institutions.
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