From Notes to Codes - Python-Driven AI for Efficient Medical Coding

Medical coding is essential for healthcare systems, yet it’s often slow and error-prone due to the complexity of translating clinical notes into standardized codes. This challenge is exacerbated by varying coding guidelines, medical jargon, and frequent changes in standards. In this talk, we’ll explore how AI, powered by Python, is transforming medical coding to improve speed and accuracy.

We'll cover Python techniques and libraries - such as LangChain, Transformers, and FastAPI - used to automate the process. You’ll learn about available open-source datasets, pre-trained models, and the role of data annotation in automating medical coding tasks. We’ll also explore whether a purely generative AI approach is sufficient, or if hybrid methods combining traditional coding with AI are more effective. By the end, you’ll understand how Python and AI are improving healthcare workflows, and where the future of AI in medical coding is headed.