FedMentalCare introduces a framework that enables LLMs to analyze mental health status while preserving patient privacy and maintaining regulatory compliance.

• Combines Federated Learning with Low-Rank Adaptation (LoRA) to fine-tune models without exposing sensitive data
• Ensures HIPAA and GDPR compliance while leveraging AI capabilities for mental health support
• Creates privacy-preserving chatbots that can effectively analyze mental health without compromising patient data
• Demonstrates how decentralized learning can address critical concerns in healthcare AI deployment

This research is vital for medical applications as it bridges the gap between advanced AI capabilities and strict healthcare privacy requirements, potentially expanding access to mental health support while maintaining data security.

FedMentalCare: Towards Privacy-Preserving Fine-Tuned LLMs to Analyze Mental Health Status Using Federated Learning Framework