Objectives: Large Language Models (LLMs) have been proposed as a solution to address high volumes of Patient Medical Advice Requests (PMARs). This study addresses whether LLMs can generate high quality draft responses to PMARs that satisfies both patients and clinicians with prompt engineering.
Materials And Methods: We designed a novel human-involved iterative processes to train and validate prompts to LLM in creating appropriate responses to PMARs.
Since 1968, the Australian Dung Beetle Project has carried out field releases of 43 deliberately introduced dung beetle species for the biological control of livestock dung and dung-breeding pests. Of these, 23 species are known to have become established. For most of these species, sufficient time has elapsed for population expansion to fill the extent of their potential geographic range through both natural and human-assisted dispersal.
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