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Information Fusion

Fusion of quantum computing and explainable AI: A comprehensive survey on transformative healthcare solutions

Shashank Sheshar Singh, Sumit Kumar, Rohit Ahuja, Jayendra Barua

Published Apr 19, 2025• 17 citations
Publisher
DOI
10.1016/j.inffus.2025.103217

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Stay ahead of the technological curve with this comprehensive, practical guide that showcases how the fusion of quantum principles and soft computing is delivering transformative solutions across finance, healthcare, and manufacturing. Quantum-Inspired Approaches for Intelligent Data Processing explores the cutting-edge fusion of quantum computing principles and soft computing techniques, unraveling the synergistic potential of these two paradigms. The book uses a comprehensive interdisciplinary approach, delving into the foundations of quantum mechanics and soft computing essentials, including fuzzy logic, genetic algorithms, and neural networks. Distinctive in its practical focus, the book showcases how this integration enhances intelligent data processing across various industries, offering tangible solutions to complex challenges. Through real-world applications, this book illuminates the transformative impact of quantum-inspired soft computing across multiple industries, from finance and healthcare to manufacturing. It incorporates case studies, examples, and market analyses, providing a holistic understanding of the subject and exploring emerging trends, challenges, and future opportunities, making it an invaluable resource for researchers and industrialists navigating the dynamic intersection of quantum computing and soft computing in intelligent data processing.
Due to its capacity to handle information in fundamentally new ways, leading to computational powers that were previously unreachable, the multidisciplinary subject of quantum computing has recently grown and attracted significant interest from both academia and industry. Quantum computing has great promise, but how exactly it will change healthcare is still largely unknown. The potential of quantum computing to transform compute-intensive healthcare tasks like drug discovery, personalized medicine, DNA sequencing, medical imaging, and operational optimization is the primary focus of this survey paper, which offers the first comprehensive analysis of quantum computing's diverse capabilities in improving healthcare systems. A new era in healthcare is on the horizon, thanks to quantum computing and AI coming together to transform complicated biological simulations, the processing of genetic data, and advances in drug development. Biological data may be extremely large and complicated, making it difficult for traditional computing tools to handle. This slows down and impairs the accuracy of medical discoveries. Combining the predictive power of AI with the exponential processing speed of quantum computers presents a game-changing opportunity to speed up biological research and clinical applications. The function of quantum machine learning in improving drug discovery molecular dynamics simulations powered by artificial intelligence is discussed in this article. Quickly modeling chemical interactions, analyzing drug-receptor binding affinities, and predicting pharmacokinetics with extraordinary precision are all possible with quantum-enhanced algorithms. To further improve disease progression prediction and therapeutic target identification, we also investigate quantum-assisted deep learning models for understanding complex biological processes like protein folding, epigenetic changes, and connections between metabolic pathways.