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Artificial Intelligence Deployment of Conversational Support (AI-DOCS): A patient acceptability study

Satheakeerthy, S.; Booth, A. E.; Widdop, L.; Evans, S.; Gluck, S.; Stretton, B.; Howson, S.; Gao, C.; Goh, R.; Gilbert, T.; Christopher Foster-McBride, C.; Chan, W. O.; Bellinge, J.; Zannettino, A.; Maddison, J.; Bacchi, S.

2025-07-24 medical education
10.1101/2025.07.19.25331814 medRxiv
Show abstract

This study evaluated an artificial intelligence (AI) system based on a large language model (LLM) in conducting complex patient assessments, comparing its acceptability to that of human basic physician trainees (BPTs) during a divisional clinical examination (DCE). Compared with BPTs, Artificial Intelligence Deployment of Conversational Support (AI-DOCS) scored similarly empathy, politeness, and comprehensiveness to human trainees. AI-DOCS also elicited important clinical information that was not divulged to human examiners. Further research is needed to explore the integration of AI-DOCS into clinical workflows.

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The top 5 journals account for 50% of the predicted probability mass.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.