This research demonstrates how specialized Large Language Models can be integrated into digital adherence technologies to enhance tuberculosis treatment through improved clinician-patient communication.

• Addresses the global TB crisis by supporting patients in low- and middle-income countries
• Augments interactive communication between patients and treatment supporters
• Helps bridge gaps caused by limited healthcare access and high patient-to-provider ratios
• Potentially improves treatment completion rates through consistent, personalized support

This innovation matters because tuberculosis remains the leading cause of death from infectious disease globally, with outcomes severely impacted by resource constraints. AI-enabled communication tools offer a scalable solution to extend the reach of limited healthcare resources.

Transforming Tuberculosis Care: Optimizing Large Language Models For Enhanced Clinician-Patient Communication