A glowing, translucent AI robot with headphones and a network overlay, in the foreground of a blurred healthcare setting with doctors.

Use Case : Healthcare UC Overview The increasing reliance on Artificial Intelligence (AI) for remote healthcare delivery has raised serious concerns about how sensitive medical data is collected, processed, and shared. Traditional cloud-based AI diagnostic systems depend heavily on centralized data aggregation, meaning that patients’ medical histories, symptoms, and diagnostic results are transmitted to a remote server for model training and inference. This approach not only creates vulnerabilities to cyberattacks and data breaches but also risks violating stringent global privacy regulations such as the GDPR in Europe and the HIPAA in the United States. To address these challenges, GWDG proposes a Privacy-Preserving LLM Chatbot for Remote Medical Diagnostics system that introduces a decentralized and privacy-preserved framework for intelligent healthcare assistance. The chatbot leverages Large Language Models (LLMs) for natural, conversational symptom analysis and diagnostic reasoning while integrating advanced privacy-preserving AI techniques to ensure that no raw personal data leaves the user’s device or hospital local edge server. Overall, this approach aims to deliver a new paradigm for trustworthy, regulation-compliant, and human-centric AI in healthcare, capable of performing advanced diagnostic reasoning without requiring patients to sacrifice their privacy. Beyond State-of-the-Art Current state-of-the-art medical AI chatbots, such as Med-PaLM, GPT-4 Health, or See more