TAMA introduces a novel human-AI collaborative framework that efficiently extracts insights from clinical interviews using multiple LLM agents working together.

• Transforms resource-intensive qualitative analysis into an efficient, scalable process
• Leverages multi-agent systems for enhanced coherence and comprehensive analysis
• Specifically tested with clinical interviews of parents with children having rare congenital heart disease
• Demonstrates how AI can support healthcare professionals while maintaining human expertise in the loop

This research represents a significant advancement for medical practitioners by reducing analysis time while maintaining quality, potentially accelerating clinical insights and improving patient care through more accessible qualitative data analysis.

TAMA: A Human-AI Collaborative Thematic Analysis Framework Using Multi-Agent LLMs for Clinical Interviews