EC Pulmonology and Respiratory Medicine

Quantum computing harnesses quantum mechanical properties to tackle computationally intensive problems beyond classical capabilities. This review explores its applications in respiratory medicine, where computational complexity has traditionally limited progress. Quantum approaches show promise in enhancing lung cancer detection through neural networks that maintain high accuracy while dramatically reducing parameter counts. Early quantum-optimized radiotherapy planning demonstrates faster treatment planning with improved targeting precision. Despite encouraging developments, significant barriers remain, including hardware limitations, integration challenges, and limited quantum computing expertise among healthcare professionals. This review provides critical perspectives on how quantum computing might transform our understanding and treatment of lung diseases as the technology evolves.

 Keywords: Quantum Computing; Lung Disease; Medical Imaging; Quantum Machine Learning; Respiratory Medicine; Cancer Detection

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