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This paper describes our submission to the MEDIQA-Chat 2023 shared task forautomatic clinical note generation from doctor-patient conversations. We reportresults for two approaches: the first fine-tunes a pre-trained language model(PLM) on the shared task data, and the second uses few-shot in-context learning(ICL) with a large language model (LLM). Both achieve high performance asmeasured by automatic metrics (e.g. ROUGE, BERTScore) and ranked second andfirst, respectively, of all submissions to the shared task. Expert humanscrutiny indicates that notes generated via the ICL-based approach with GPT-4are preferred about as often as human-written notes, making it a promising pathtoward automated note generation from doctor-patient conversations.

WangLab at MEDIQA-Chat 2023: Clinical Note Generation from Doctor-Patient Conversations using Large Language Models