Large language models accurately extract aortic information from abdominal imaging reports in a large, real-world database

Abstract

LLM extraction of aortic information from abdominal imaging reports is exceptionally reliable without the need for additional human-directed training. In general, LLMs allow for flexible and efficient data mining with minimal human effort. Many LLMs are publicly available and incur no processing costs, making them easily accessible and cost-effective tools to decrease the administrative burden of running complex AAA surveillance registries, with the added opportunity to improve the quality and efficiency of clinical research in the field.

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