MACHINE-LEARNING-BASED WORKFLOW PLATFORM

Abstract: a machine learning-based clinical workflow system processes patient encounter data to generate structured data records and predicted diagnosis classification codes. the system may obtain an input record, generate vector embeddings, and identify reference records using vector similarity operations. a machine learning (ml) component may generate a structured data record based on the input and reference records. the system may also generate an ml instruction, identify reference codes, and produce a predicted code. the predicted code may include a predicted diagnosis classification code, a predicted procedural code, or a billing code. vector databases storing embeddings of medical codes and records may facilitate efficient retrieval of relevant information. some implementations may include prediction of billing codes to address revenue capture. some implementations may utilize specialty-specific processes and data to enhance accuracy for particular medical fields. the system may incorporate clinician feedback to continuously improve performance and adapt to evolving healthcare practices.

Inventor(s): Caroline Chai Zhang, Jocelyn Lillian Kang

CPC Classification: G16H40/20 (for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms)

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