Useful large language models in health are not miraculous. #AIHealthcare

Large language models in health: useful, not a miracle cure

Large language models (LLMs) are gaining traction in healthcare, but they are not a magic solution to all problems. LLMs rely on high-quality data and lack reasoning capabilities, limiting their use in healthcare tasks. The Australian e-Health Research Centre (AEHRC) is working on safely implementing LLMs and other AI tools in healthcare to optimize services for Australians. Generative AI, a widely used type of AI, creates content in response to user prompts. LLMs, a type of generative AI, can recognize, translate, summarize, predict, and generate text-based content by analyzing patterns in data.

Neural networks, the brains of AI, are trained to perform tasks like language generation. LLMs are based on a transformer architecture with layers that analyze text input and predict the next word. While LLMs are not a cure-all solution for healthcare, they can be helpful. AEHRC has developed LLM-based chatbots for healthcare settings to support patients and clinicians. Safety and ethical use of LLMs and AI in healthcare are crucial, with regulations in place to ensure safe and ethical use.

Collaboration with researchers, clinicians, carers, technicians, health services, and patients is essential to ensure that AI technologies are fit for purpose in the complex healthcare system. While LLMs may not solve all healthcare problems, they can improve efficiency, support patients and clinicians, and ease the burden on the healthcare system. The goal is to create a future where AI improves healthcare and is widely understood and trusted by all.

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