Quantum computing has heralded a new era of computational capabilities, enabling the resolution of complex problems that are intractable for classical computers. The health care sector, renowned for its data-rich and computationally intensive challenges, stands to benefit significantly from quantum-based algorithms. This research paper surveys the current landscape of quantum algorithm applications in health care, emphasizing their potential in simulation modeling, decision support, adversarial robustness, and cross-domain recommendations. By integrating findings from recent literature, this survey critically examines both the opportunities and limitations inherent to quantum-driven approaches in health care. The paper provides an in-depth literature review, methodology for categorizing quantum algorithmic applications, a discussion of empirical and simulated results, and concludes with insights for future research. This work aims to serve as a comprehensive reference for researchers and practitioners seeking to understand and develop quantum-based solutions in health care.
Quantum computing has heralded a new era of computational capabilities, enabling the resolution of complex problems that are intractable for classical computers. The health care sector, renowned for its data-rich and computationally intensive challenges, stands to benefit significantly from quantum-based algorithms. This research paper surveys the current landscape of quantum algorithm applications in health care, emphasizing their potential in simulation modeling, decision support, adversarial robustness, and cross-domain recommendations. By integrating findings from recent literature, this survey critically examines both the opportunities and limitations inherent to quantum-driven approaches in health care. The paper provides an in-depth literature review, methodology for categorizing quantum algorithmic applications, a discussion of empirical and simulated results, and concludes with insights for future research. This work aims to serve as a comprehensive reference for researchers and practitioners seeking to understand and develop quantum-based solutions in health care.
The field of quantum computing has rapidly evolved in an interdisciplinary approach, calling for significant attention from academia and industry alike in recent years. This interest is largely due to the fact that quantum computers utilize the principles of quantum mechanics to compute and manipulate information, which offers capabilities and speeds (for specific, particularly complicated) computations that are beyond the capabilities of traditional computers. While the potential of quantum computing offers much promise, it has not yet been fully explored within the health care sector; the field remains in its early stages of development. This work investigates the impact of quantum computing on modern health care systems by focusing specifically on its transformative potential in performing computationally- intensive tasks such as drug discovery, precision and personalized medicine, DNA sequencing strategies, high-definition medical imaging, and managing health care operations more efficiently. In addition, this survey presents an all-encompassing view of how quantum computing will be used in healthcare and will serve as an excellent resource. The survey intends to promote greater insight into the state of the current research landscape while identifying critical opportunities and deficiencies that impact future decisions regarding the development of nextgeneration quantum-enabled healthcare solutions.
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
In recent years, the interdisciplinary field of quantum computing has rapidly developed and garnered substantial interest from both academia and industry due to its ability to process information in fundamentally different ways, leading to hitherto unattainable computational capabilities. However, despite its potential, the full extent of quantum computing’s impact on healthcare remains largely unexplored. This survey paper presents the first systematic analysis of the various capabilities of quantum computing in enhancing healthcare systems, with a focus on its potential to revolutionize compute-intensive healthcare tasks such as drug discovery, personalized medicine, DNA sequencing, medical imaging, and operational optimization. Through a comprehensive analysis of existing literature, we have developed taxonomies across different dimensions, including background and enabling technologies, applications, requirements, architectures, security, open issues, and future research directions, providing a panoramic view of the quantum computing paradigm for healthcare. Our survey aims to aid both new and experienced researchers in quantum computing and healthcare by helping them understand the current research landscape, identifying potential opportunities and challenges, and making informed decisions when designing new architectures and applications for quantum computing in healthcare.
Quantum computing is an emerging paradigm that will soon transform the face of several industries, such as health care. This paper focuses on applying quantum computing in optimizing analytics on healthcare data, especially amidst big data challenges in the digital age. A health system generates tremendous amounts of complex datasets requiring advanced tools to draw meaningful insights from such data. Traditionally, most of these methods fail to meet the demands for real-time processing, predictiveness, and data security. Taking leaps with extraordinary computing power from quantum computing, health analytics can be taken towards leaps of revolutionary precision in medicine, resource allocation, and early detection of diseases. This paper explains how quantum algorithms synergistically find applications in health data. Areas of applicability, technological constraints, and issues related to ethics form other emphases. This, in turn, provides a comprehensive literature review, a method for quantum-enhanced analytics, and an analysis of the results of simulated quantum experiments, which points toward this integration as transformative. Furthermore, an architectural framework for quantum-driven healthcare systems, as depicted in the study, is postulated. The results are illustrated, including figures and corresponding tables for descriptive performance benefits and challenges. Implications to clinical workflows, patient outcomes, and the larger health ecosystem are demonstrated in the discussion. The conclusion presents the limitations and avenues for further research focusing on interdisciplinarity with quantum computing for the best healthcare.
The purpose of this paper is to provide an overview of the current state quantum computing in medical laboratory science, from ancient methodologies to the present applications and future prospects. Quantum computing has the potential to revolutionize a wide range of industries, including health care, by greatly enhancing the speed and accuracy of various tasks such as drug discovery, personalized medicine, and medical imaging and medical laboratory diagnosis. A literature review of the existing literature on the use of quantum computing in the health sector is conducted, revealing the various applications of quantum computing in the health sector and the current state of research in this area. This paper concludes that while the technology is still in its early stages of development, quantum computing has the potential to revolutionize the health sector; however, further studies are needed to fully understand the implications of quantum computing in health care, mostly in the field of medical laboratory science.
The combination of Quantum Technologies and Artificial Intelligence (AI) is shaping a new approach in life sciences and healthcare. The growing complexity of biomedical data, along with the demand for quick and precise decision-making, has led to the exploration of new computing methods beyond traditional systems. AI has shown great success in medical diagnosis, disease prediction, drug discovery, and healthcare analytics. However, traditional AI models have drawbacks when it comes to optimization, scalability, and computational efficiency. Quantum technologies offer new computing principles based on quantum mechanics, allowing for parallel processing and better optimization. This review provides a detailed look at recent progress in quantum technologies and AI applications within life sciences and healthcare. The paper examines the basics of quantum computing, quantum-inspired algorithms, and hybrid quantum-AI frameworks, emphasizing their uses in disease diagnosis, medical imaging, genomics, molecular modeling, and drug discovery. It also discusses current challenges, practical limitations, and future research directions. This review aims to give researchers, students, and practitioners a clear understanding of the developing quantum-AI landscape and its potential effects on future healthcare systems.