Murphy D C, Saleh D B
Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK.
Institute of Genetic Medicine, Newcastle University, Newcastle Upon Tyne, UK.
Ann R Coll Surg Engl. 2020 Oct;102(8):577-580. doi: 10.1308/rcsann.2020.0158. Epub 2020 Aug 11.
An increasing quantity of data is required to guide precision medicine and advance future healthcare practices, but current analytical methods often become overwhelmed. Artificial intelligence (AI) provides a promising solution. Plastic surgery is an innovative surgical specialty expected to implement AI into current and future practices. It is important for all plastic surgeons to understand how AI may affect current and future practice, and to recognise its potential limitations.
Peer-reviewed published literature and online content were comprehensively reviewed. We report current applications of AI in plastic surgery and possible future applications based on published literature and continuing scientific studies, and detail its potential limitations and ethical considerations.
Current machine learning models using convolutional neural networks can evaluate breast mammography and differentiate benign and malignant tumours as accurately as specialist doctors, and motion sensor surgical instruments can collate real-time data to advise intraoperative technical adjustments. Centralised big data portals are expected to collate large datasets to accelerate understanding of disease pathogeneses and best practices. Information obtained using computer vision could guide intraoperative surgical decisions in unprecedented detail and semi-autonomous surgical systems guided by AI algorithms may enable improved surgical outcomes in low- and middle-income countries. Surgeons must collaborate with computer scientists to ensure that AI algorithms inform clinically relevant health objectives and are interpretable. Ethical concerns such as systematic biases causing non-representative conclusions for under-represented patient groups, patient confidentiality and the limitations of AI based on the quality of data input suggests that AI will accompany the plastic surgeon, rather than replace them.
需要越来越多的数据来指导精准医疗并推动未来的医疗实践,但当前的分析方法常常不堪重负。人工智能(AI)提供了一个很有前景的解决方案。整形手术是一个创新性的外科专业,有望在当前及未来的实践中应用AI。对于所有整形外科医生而言,了解AI如何影响当前及未来的实践,并认识到其潜在局限性非常重要。
对同行评审的已发表文献和在线内容进行了全面综述。我们根据已发表的文献和持续的科学研究报告了AI在整形手术中的当前应用以及未来可能的应用,并详细阐述了其潜在局限性和伦理考量。
当前使用卷积神经网络的机器学习模型能够评估乳房钼靶检查,并像专科医生一样准确地区分良性和恶性肿瘤,运动传感器手术器械可以整理实时数据以提供术中技术调整建议。预计集中式大数据门户将整理大型数据集,以加速对疾病发病机制和最佳实践的了解。使用计算机视觉获得的信息可以以前所未有的详细程度指导术中手术决策,由AI算法引导的半自主手术系统可能会在低收入和中等收入国家实现更好的手术效果。外科医生必须与计算机科学家合作,以确保AI算法服务于临床相关的健康目标且具有可解释性。诸如系统偏差导致对代表性不足的患者群体得出非代表性结论、患者隐私以及基于数据输入质量的AI局限性等伦理问题表明,AI将与整形外科医生同行,而不是取代他们。