Quantum computing revolution in healthcare: a systematic review of applications, issues and future directions

Document Type

Article

Publication Title

Artificial Intelligence Review

Abstract

Conventional treatment methods make even the most basic healthcare issues more complicated, which in turn increases the number of parties involved. Classical computing lacks the speed and accuracy needed for effective stakeholder collaboration in COVID-19 healthcare solutions, such as patients, insurance agents, healthcare practitioners, pharmaceutical suppliers, etc. The research uses organizational information processing theory (OIPT) to examine how quantum computing which is applications of artificial intelligence (AI) could transform the healthcare business, creating a more sustainable and less burdened system. The study of quantum computing (QC) has the potential to bring about “quantum leaps,” which might have unforeseen consequences for healthcare. The discovery of new medications, the personalization of medicinal treatments, and the acceleration of DNA sequencing are just a few of the many possible applications of this method. The potential of QC 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 QCs diverse capabilities in improving healthcare systems. After a thorough literature study, we created taxonomies on the healthcare QC paradigm’s history and supporting technologies, applications, needs, architectures, security, outstanding questions, and future research prospects. We hope that by conducting this survey, researchers with varying levels of experience in quantum computing and healthcare will better understand the state of the art, assess opportunities and threats, and make informed decisions as they develop novel architectures and applications for this emerging field.

DOI

10.1007/s10462-025-11381-w

Publication Date

12-1-2025

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