AI RESEARCH
Training a Large Language Model for Medical Coding Using Privacy-Preserving Synthetic Clinical Data
arXiv CS.CL
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ArXi:2603.23515v1 Announce Type: new Improving the accuracy and reliability of medical coding reduces clinician burnout and s revenue cycle processes, freeing providers to focus on patient care. However, automating the assignment of ICD-10-CM and CPT codes from clinical documentation remains a challenge due to heterogeneous records, nuanced coding guidelines, and long-tail distributions. Large language models have been proposed to help or automate specific medical coding tasks.