Uncovering bias and variability in how large language models attribute cardiovascular risk

Large language models (LLMs) are used increasingly in medicine, but their decision-making in cardiovascular risk attribution remains underexplored. This pilot study examined how an LLM apportioned relative cardiovascular risk across different demographic and clinical domains. A structured prompt set across six domains was developed, across general cardiovascular risk, body mass index (BMI), diabetes, depression, smoking, […]

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