Quantum-ML and Gen-AI in Preliminary Disease Diagnosing: A Chatbot Framework

Abstract

The advent of Generative Artificial Intelligence (GenAI) has significantly impacted various industries, including healthcare. This paper presents an advanced Healthcare Chatbot leveraging Large Language Models (LLMs) for preliminary disease diagnosis. Traditional healthcare systems, especially in remote areas, struggle with accessibility and timely intervention. By integrating GenAI models, our chatbot enhances patient interactions, symptom analysis, and early medical insights. Additionally, we use a parameterized quantum circuit to integrate Quantum Machine Learning-based embeddings in order to improve semantic retrieval and alleviate the dimensionality bottleneck of classical embeddings. By introducing entanglementbased encoding, this quantum-enhanced vectorization improves robustness and generalization in low-dimensional latent space. This kind of integration shows how QML and GenAI work together to create healthcare dialogue systems that are effective, scalable, and contextually aware.

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