This invention describes a computer system that reads clinical notes to automatically generate medical codes. It uses natural language processing to break down the text, identify key medical concepts, and match them to a structured medical dictionary. These concepts are then converted into characters and placed into specific slots to form a medical code, specifically segmenting text based on existing document boundaries.
Why it matters: Filed before the widespread adoption of advanced LLMs. These models could now significantly enhance the accuracy and scalability of the semantic mapping and text segmentation described, potentially reducing the manual effort in ontology development.
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