Suzanne M Skevington, Rachel Day, Alison Chisholm, Paul Trueman
How much do doctors use quality of life information in primary care? Testing the trans-theoretical model of behaviour change
Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation
large language models llms offer significant potential medical information extraction carry risks generating incorrect information study aims develop validate retrieveraugmented generation rag model provides accurate medical knowledge diabetes diabetic foot care laypersons eighthgrade literacy level improving health literacy patient education paramount addressing problem limb loss diabetic population addition affecting patient wellbeing improved outcomes improved physician wellbeing important outcome selfmanagement model patient health education used rag architecture built questionandanswer artificial intelligence ai model extract knowledge response questions pertaining diabetes diabetic foot care utilized gpt4 openai pinecone vector database nih national standards diabetes selfmanagement education served basis knowledge base models outputs validated expert review established guidelines literature fiftyeight keywords used select 295 articles model tested 175 questions across topics study demonstrated appropriate content volume fewshot learning prompts rag model achieved 98 accuracy confirming capability offer userfriendly comprehensible medical information rag model represents promising tool delivering reliable medical knowledge public used selfeducation selfmanagement diabetes highlighting importance content validation innovative prompt engineering ai applications