The complexities of patient-centred conversational artificial intelligence
Consumer-facing health chatbots powered by large language models (LLMs) are increasingly used for symptom assessment. However, chatbot development and evaluation often rely on cooperative, articulate, simulated patients. We analysed 2,053 real patient-chatbot conversations and found that communication patterns and expression of emotions vary widely across users. We developed a patient simulator that separately models clinical content, emotional state, conversational strategy, and communication style. In a Turing-inspired evaluation of realism with 15 human graders, simulated conversations were
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- LinkedLinked via arxiv author · 85%João Matos →
“The complexities of patient-centred conversational artificial intelligence”
- LinkedLinked via arxiv author · 85%Olivia Buege →
“The complexities of patient-centred conversational artificial intelligence”