This chapter discusses about how quantum computing has changed the healthcare field, focusing on its basic ideas of superposition and entanglement, which make it possible for computers to do more than traditional ones. It goes into detail about some of the most important uses, like using molecular simulations to find new drugs faster, using quantum-enhanced data analysis for personalized medicine, improving medical imaging, enhancing healthcare processes, and coming up with new ways to model diseases. Despite these positive changes, the chapter examines the problems that still need to be resolved. These include hardware limits, quantum error correction, system integration, data protection, and changing legal environments. It also shows how important it is to consider ethics and ensure everyone has equal access. At the end of the chapter, it is emphasized how important it is for people from different fields to work together, for artificial intelligence (AI) to be integrated, and for investments to continue so that quantum computing can fully transform diagnoses, treatment plans, and healthcare services as a whole.
This chapter discusses about how quantum computing has changed the healthcare field, focusing on its basic ideas of superposition and entanglement, which make it possible for computers to do more than traditional ones. It goes into detail about some of the most important uses, like using molecular simulations to find new drugs faster, using quantum-enhanced data analysis for personalized medicine, improving medical imaging, enhancing healthcare processes, and coming up with new ways to model diseases. Despite these positive changes, the chapter examines the problems that still need to be resolved. These include hardware limits, quantum error correction, system integration, data protection, and changing legal environments. It also shows how important it is to consider ethics and ensure everyone has equal access. At the end of the chapter, it is emphasized how important it is for people from different fields to work together, for artificial intelligence (AI) to be integrated, and for investments to continue so that quantum computing can fully transform diagnoses, treatment plans, and healthcare services as a whole.
The use of quantum computing1 in healthcare represents a significant shift with the potential to revolutionize medical research, diagnostics, and treatment. Quantum computing can process and analyze large datasets much faster than classical computing, offering new opportunities in healthcare. This paper examines the various ways quantum computing can be applied in healthcare, such as in drug discovery, genetic research, personalized medicine, and complex disease modeling. By using quantum algorithms, researchers can identify new treatment targets and simulate the effects of drugs on human biology in ways that were previously impossible, which can reduce the time and cost of bringing new drugs to market. Quantum computing also allows for analyzing large genomic datasets2, which can help tailor treatments to individual genetic profiles. Additionally, this technology helps in modeling complex biological systems and disease processes, providing insights into the mechanisms of diseases at a molecular level and enabling the development of more effective treatments. However, integrating quantum computing into healthcare comes with challenges such as technical limitations, the need for specialized expertise, data security concerns, and ethical considerations. This paper provides a comprehensive overview of the potential applications of quantum computing in healthcare, addresses the associated challenges, and discusses the future directions of this growing field, emphasizing the importance of interdisciplinary collaboration in fully utilizing quantum technologies in medicine. In recent years, quantum computing has rapidly advanced and attracted significant interest from academia and industry due to its unique ability to process information differently, resulting in previously unattainable computational capabilities. Despite its potential, the full impact of quantum computing on healthcare has not been thoroughly explored. This survey paper provides a systematic analysis of quantum computing's various capabilities in improving healthcare systems, focusing on its potential to transform compute-intensive healthcare tasks such as drug discovery, personalized medicine, DNA sequencing4, medical imaging5, and operational optimization. Through a comprehensive review of existing literature, we have developed taxonomies6 covering different aspects, including background and enabling technologies, applications, requirements, architectures, security, open issues, and future research directions, offering a comprehensive view of the quantum computing paradigm for healthcare. Our survey aims to assist new and experienced researchers in quantum computing and healthcare by helping them comprehend the current research landscape, identify potential opportunities and challenges, and make informed decisions when developing new architectures and applications for quantum computing in healthcare
Transformative impact and change can be acquired by quantum computing in the field of medical sciences and clinical care. This chapter explores the revolutionary prospects of quantum physics, that is, superposition and entanglement, with its application in medical sciences and healthcare. Additionally, a comprehensive framework of the technology is presented in this chapter in the facets of quantum artificial intelligence applications, drug discovery, personalized treatment, biomarker discovery, and data management. The chapter examines the concepts from quantum computing to advanced healthcare from next-generation applications. Despite a transforming potential, challenges due to technical complexities, ethical and regulatory concerns, high cost, and limited accessibility from the unification of quantum computing with healthcare are also presented. A practical roadmap is discussed at the end of the chapter to integrate multidisciplinary technologies for creating smart quantum healthcare solutions. Actionable insights are offered in the section for healthcare and biomedical scientists, healthcare providers, pharmaceutical and biotechnological companies, public health management, and startup companies to dive into the possibilities that quantum computing can provide in healthcare.
The healthcare sector faces complex challenges that call for innovative solutions to improve diagnostic accuracy, treatment efficacy, and data management. Quantum computing, with its unique capabilities, holds the potential to revolutionize various aspects of healthcare. This narrative review critically examines the existing literature on the application of quantum computing in healthcare, focusing on its utility in enhancing diagnostics, data processing, and treatment planning. Quantum computing's ability to handle large, complex datasets more efficiently than classical computers can significantly impact domains such as genomics, medical imaging, and personalized medicine. Quantum algorithms can accelerate the identification of genetic markers associated with diseases, facilitate the analysis of medical images, and optimize treatment plans based on individual genetic profiles. Moreover, quantum cryptography offers a robust security solution for safeguarding sensitive patient data, a critical need as healthcare increasingly relies on digital platforms. Despite the promising outlook, the integration of quantum computing into healthcare faces technical, ethical, and regulatory challenges. The delicate nature of quantum hardware, the need for error correction, and the scalability of quantum systems pose barriers to widespread adoption. Additionally, concerns around patient privacy and data security, as well as the need for updated regulatory frameworks, must be addressed. Ongoing research and collaborative efforts involving researchers, healthcare providers, and technology developers are crucial to overcoming these hurdles and realizing the full potential of quantum computing in transforming healthcare. As quantum computing continues to evolve, its impact on the future of healthcare could be profound, leading to earlier disease detection, more personalized treatments, and improved patient outcomes. For instance, quantum computing has already been applied to enhance drug discovery processes, with companies like D-Wave Systems (Burnaby, Canada) demonstrating faster molecular simulations for pharmaceutical research and IBM's (Armonk, USA) quantum systems being used to model chemical reactions for new drug development.
This chapter introduces the foundations of quantum computing and explains why it is poised to reshape modern healthcare. It outlines how quantum principles such as superposition and entanglement enable new forms of computation that can address the growing complexity of medical data, scientific discovery, and clinical decision-making. The chapter explores practical applications across drug discovery, personalized medicine, medical imaging, diagnostics, hospital operations, and data security, showing how quantum systems could solve challenges that exceed the limits of classical computing. Readers are guided through the evolving landscape of hardware, algorithms, workflow integration, and ethical considerations that will shape adoption in clinical and research environments. By the end of the chapter, readers will understand both the transformative potential and the practical constraints of quantum computing, gaining insight into how this emerging technology may support faster discovery, more precise care, stronger security, and more efficient healthcare systems.
Quantum computing is a developing computational paradigm that uses the principles of quantum mechanics, like superposition and entanglement, to execute composite calculations beyond the abilities of conventional computers. Currently, implementation of this technology in medicine has the potential to revolutionize various domains like drug discovery, protein folding, genomics, medical imaging, and personalized healthcare. By allowing high-dimensional data processing and accurate molecular simulations, quantum computing may enhance biomedical research and thereby improving clinical decision-making. Moreover integrating quantum computing with artificial intelligence, mainly through quantum machine learning, further accelerates its capability to assess vast complex biological datasets and generate precise predictive models. Applications like disease prediction, drug response optimization, and advanced diagnostic imaging further validates its growing importance in modern healthcare. However, the implementation of quantum computing in medicine is presently limited by technical challenges, that includes decoherence, error correction, and scalability, as well as practical problems like high budgets and lack of skilled professionals. Moreover, ethical concerns play a major hurdle related to data privacy and healthcare inequality also require cautious consideration. In spite of these challenges, ongoing developments in hybrid quantum-classical systems and quantum algorithms reveal that a promising future, particularly placing quantum computing as an effective transformative force in next-generation medicine.
Quantum computing, an interdisciplinary area that processes data in fundamentally different ways, has recently grown and attracted a lot of attention from academics and businesses alike because of its potential to achieve computational powers that were previously unimaginable. Quantum computing's potential in the medical field has not been thoroughly explored as yet. Computing at the quantum level has the potential to revolutionize computationally intensive healthcare applications such as personalized medicine, drug discovery, medical imaging, DNA sequencing, and operational optimization. This review article provides the first all- encompassing examination of the many applications of quantum computing to healthcare systems, focusing on these specific domains. Many different areas are covered by our taxonomies, such as foundational and enabling technologies, applications, needs, architectures, security, open problems, and potential avenues for future study. The outcome of this thorough literature study is an all-encompassing perspective on the quantum computing paradigm as it pertains to healthcare. Synthetic intelligence (AI) and quantum computing are about to converge, and this article delves into how that can change the face of healthcare. In this study, we take a look at how quantum physics might help us understand how to improve AI for faster drug development, more precise clinical diagnostics, and more tailored treatment plans. The investigation probes the means by which molecular-level quantum simulations can represent complicated organic processes, enabling the unprecedented prediction of treatment interactions and the design of medicine. Also covered in the article is the idea of using quantum sensors in conjunction with AI to provide better clinical imaging that can pick up on more widespread problems. Highlighting its role in bringing in a new technology of personalized medicinal drug and efficient drug improvement, this synergy is discussed for its transformational power.