Medical LLMs for Clinical Text Summarization, Information Extraction, and Question Answering

Large language models like GPT-4 and their open-source counterparts provide a leap in capabilities on understanding medical language and context - from passing the US medical licensing exam to summarizing clinical notes. Recently, a wave of health-specific large language models shows that tuning models specifically on medical data and tasks can result in even higher accuracy on everyday use cases such as question answering, information extraction, and summarization. Some of these models also aim to address the privacy, hallucination, and fairness issues that current language models exhibit.