Fairburn Stevan C, Jehi Lara, Bicknell Brenton T, Wilkes Beckley G, Panuganti Bharat
Marnix E. Heersink Institute for Biomedical Innovation, University of Alabama at Birmingham, Birmingham, AL, United States.
UAB Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States.
Front Med (Lausanne). 2025 Apr 23;12:1573016. doi: 10.3389/fmed.2025.1573016. eCollection 2025.
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.
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.
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.
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.
本综述探讨量子计算（QC）在临床护理中的应用，重点关注直接影响患者预后的进展。量子计算在医学领域具有变革潜力，特别是通过提高诊断准确性、优化治疗方案和实现实时决策。
对2015年至2024年间发表的35项研究进行了系统分析。评估这些研究对量子计算技术在临床护理中诊断、治疗和决策支持改善方面的贡献。
分析表明量子计算有望提高医学成像的诊断准确性、优化肿瘤学治疗并增强实时临床决策。量子计算驱动的算法显示出提高诊断准确性和计算效率的潜力。这些改进能够更早地检测出阿尔茨海默病、癌症和骨关节炎等疾病，支持更及时的干预并改善预后。
尽管取得了令人鼓舞的成果，但当前的限制，如硬件可扩展性、错误缓解和伦理考量，阻碍了量子计算在临床环境中的广泛应用。克服这些挑战需要跨学科合作和技术创新。该综述强调了量子计算提供精确、个性化和高效护理的能力，主张将其整合到医疗工作流程中，以推进精准医学并改善患者预后。
