This Focus Session introduces participants to next-generation Generative AI for teaching clinical and communication skills in healthcare education. Building on the freely available AI Patient Actor, we demonstrate enhanced capabilities including voice-native interactions, personality modeling, and prosody analysis. The AI Patient Actor provides scalable opportunities for diagnostic reasoning practice, allowing students to conduct comprehensive histories, gather clinical information, and develop differential diagnoses through realistic patient interactions. Medical educators will learn to create distinct patient personalities with unique emotional profiles and communication styles for both diagnostic and communication training. For diagnostic skills, the AI presents symptoms, responds to clinical questions, and provides examination findings that challenge students' diagnostic understanding and clinical reasoning. For communication training, voice-native capabilities enable emotionally nuanced interactions where prosody analysis provides feedback on students' tone, pace, and emotional resonance, teaching not just what to say but how to say it. Participants will engage hands-on with the platform, creating patient personalities ranging from anxious teenagers to stoic elderly patients, each requiring different communication approaches. We'll explore how the AI supports iterative diagnostic practice while separately developing empathetic communication through voice analysis. By session's end, participants will understand how to leverage these distinct but complementary features: AI patients for unlimited diagnostic reasoning practice and voice/prosody analysis for mastering the subtle art of clinical communication.

Learning Outcomes

1. Understand AI Patient Actors for diagnostic reasoning training: Participants will learn how the AI Patient Actor enables students to practice history-taking, clinical reasoning, and differential diagnosis development through unlimited interactions with virtual patients presenting diverse clinical scenarios.
2. Master voice-native AI for communication skills: Participants will gain hands-on experience with voice-to-voice AI interactions that convey emotional nuance, understanding how prosody analysis helps students develop empathetic communication by providing feedback on tone, pace, and emotional presence.
3. Create diverse patient personalities: Participants will design multidimensional patient characters with distinct traits, emotional profiles, and cultural backgrounds, useful for both diagnostic reasoning exercises and communication skills training across various clinical contexts.
4. Apply prosody analysis for communication excellence: Participants will use AI-powered voice analysis tools that evaluate delivery, providing students with actionable feedback on their non-verbal communication skills and bedside manner.
5. Integrate AI tools across clinical curricula: Participants will develop strategies for implementing the open-access AI Patient Actor for diagnostic reasoning practice in basic science and clinical courses, ensuring these technologies complement existing educational approaches.