Applications of quantum computing in clinical care.

INTRODUCTION

This review examines quantum computing (QC) applications in clinical care, emphasizing advancements directly impacting patient outcomes. QC holds transformative potential in medicine, particularly through enhancing diagnostic accuracy, optimizing treatment plans, and enabling real-time decision-making.

METHODS

A systematic analysis of 35 studies published between 2015 and 2024 was conducted. The studies were evaluated for their contributions to diagnostic, therapeutic, and decision-support improvements in clinical care enabled by quantum computing technologies.

RESULTS

The analysis revealed QC's promise in improving diagnostic accuracy in medical imaging, optimizing treatments in oncology, and enhancing real-time clinical decision-making. QC-driven algorithms demonstrated potential to enhance diagnostic accuracy and computational efficiency. These improvements could enable earlier detection of diseases such as Alzheimer's, cancer, and osteoarthritis, supporting more timely interventions and better prognoses.

DISCUSSION

Despite promising outcomes, current limitations-such as hardware scalability, error mitigation, and ethical considerations-hinder widespread adoption of QC in clinical settings. Overcoming these challenges will require interdisciplinary collaboration and technological innovation. The review underscores QC's capacity to deliver precise, personalized, and efficient care, advocating for its integration into healthcare workflows to advance precision medicine and improve patient outcomes.