Quantum-enhanced AI: Shaping the future of Healthcare 

Healthcare is generating increasingly complex data across electronic health records, medical imaging, wearable devices, and genomic platforms. While AI is transforming diagnosis, clinical decision support, and personalized care, the scale and complexity of biomedical data are pushing traditional computing to its limits. Quantum-enhanced artificial intelligence brings together AI and quantum computing to explore new possibilities for faster, more sophisticated healthcare analytics.  

Unlocking new possibilities with quantum AI 

This whitepaper examines how quantum computing concepts such as superposition and entanglement can complement AI to address computationally intensive healthcare use cases. It explores applications across drug discovery, genomic analysis, medical imaging, predictive Healthcare, and clinical decision support, where hybrid quantum-classical approaches could enable more efficient analysis and optimization. 

A hybrid approach to healthcare intelligence 

The paper presents a hybrid quantum-AI framework spanning healthcare data acquisition, preprocessing, classical AI, quantum optimization, and clinical decision support. This approach combines established machine learning capabilities with emerging quantum technologies to support advanced healthcare analytics.  

Preparing for the next era of Healthcare 

Beyond opportunities, the white paper examines current limitations, including quantum hardware maturity, integration, data privacy, algorithmic bias, transparency, and responsible AI. It also outlines future research priorities for developing scalable quantum-AI architectures that could support more personalized, predictive, and efficient healthcare systems.