Integrating Quantum Machine Learning and Deep Learning for Enhanced Lung Cancer Detection

Lung cancer is still one of the most lethal cancers in the world.Many patients are diagnosed with lung cancer in the advanced stages of the disease because early symptoms are often neglected and current diagnostic practices are unable to integrate these various information types into a single framework.Manual interpretation of the CT scan images, as well as conventional machine-learning-based diagnostic models, are typically slow, require considerable expert evaluation and consultation, and do not guide personalized treatment.The following paper defines and describes an artificial intelligence (AI)-based solution called OncoQure that adds value to these diagnostic processes by incorporating CT scan imaging, tumor characteristics, biomarker data, and patient metadata into a single system.The OncoQure platform allows for early identification of cancer and treatment approaches by automatically analyzing the medical images, estimating the likelihood of cancer based on the presenting symptoms and recommending treatment choices against the combined clinical and biological attributes of the patient.Preliminary testing of the OncoQure platform shows improved diagnostic reliability, reduced manual effort, and a better means of supporting clinicians than standard approaches.OncoQure mitigates the limitations of current diagnostic practices by offering a solution that considers different cancer diagnostic elements into one framework.