Artificial Intelligence–Enhanced Quantum Computing for Medical Simulations: Accelerating Drug Discovery, Protein Folding, and Personalized Healthcare with Performance Optimization and Predictive Accuracy
Abstract
Artificial Intelligence (AI) and Quantum Computing together are going to transform medical research, diagnostics and the simulation of treatment. Although it has already been applied to medical imaging, drug discovery and predictive analytics, AI needs large amounts of computations that are sometimes beyond the capacity of more traditional computing. Quantum computers due to their capability to do parallel processing over quantum states can be fast and efficient in unprecedented ways. The paper will discuss the combination of AI and quantum computing in the medical field, including the characterization of medical applications of AI where it complements quantum computing, an overview of the current medical applications of AI and quantum computing, and real-time diagnostics, genomics, drug discovery, molecular dynamics, and personalized medicine. We discuss the current issues state-of-art including quantum error correction, interpretability of models, and ethical implications and point toward future opportunities including digital twins, federated learning using quantum resources, and hybrid quantum-classical models. The eventuality of this integration might end up speeding up medical simulations, decreasing the expense of drug development and enhancing the patient outcomes across the globe.
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