Journal articles
This article summarises the robotic surgical systems currently available and discusses the role of automation and artificial intelligence in designing the ideal surgical robot. Two of the authors’ examples are utilised to highlight the strengths and limitations of existing deep learning models and the key challenges of big data handling and storage are briefly discussed.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7768095/ (free)
This article discusses in more detail the role of artificial intelligence in surgery. It highlights the difficulties inherent in developing deep learning models for the dynamic surgical environment and the data capture required to train such models. The role of augmenting existing surgical expertise through artificial intelligence (AI)-assisted decision making is discussed, as well as the integration of AI with the operating room environment.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6216754/ (free)
This article provides a comprehensive summary of currently available robotic surgical systems and provides a timeline for their clinical use. The authors give a comprehensive summary of many of the novel devices coming to market across the full range of surgical specialties. The pros and cons of augmented haptic feedback and research ideas are also discussed, along with the role of nanorobotics in delivering targeted therapies.
https://journals.sagepub.com/doi/full/10.5772/60133/ (free)
This article explores the breakdown of subtypes of robotic systems, giving examples of each in clinical practice. Older and discontinued robots are also reviewed, giving the reader a perspective on the rapid development of these technologies over the past 30 years. Guidance systems and catheter-based devices are discussed in detail, as well as intelligence-based augmentation and avenues for future development and research.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7263339/ (free)
This article provides a detailed focus on spinal surgery and outlines the development of image-guided systems from fluoroscopic two-dimensional images to three-dimensional (3D) platforms utilising computed tomography (CT)/fluoroscopic imaging. Although the article is specialty specific, it very nicely explores the concept of ‘total navigation’ and the ideal of robotic systems that combine passive robotic navigation with active 3D image guidance. The role of augmented and virtual reality are also highlighted with excellent associated graphics and operative images.
https://breast-cancer-research.biomedcentral.com/articles/10.1186/s13058-017-0845-2/ (free)
This research manuscript explores novel ‘intelligent knife’ (iKnife) technology and its role in the assessment of oncological margins. Although this can be applied in both minimally invasive and open surgery, if clinically validated in large prospective studies, such technologies may revolutionise the future of cancer surgery with real-time assessment of tumour margins and be integrated with other augmented reality systems. The work highlights the possibilities of current technological advances and paves the way for further ideas and development.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5009165/ (free)
This meta-analysis is the largest published pan-specialty appraisal of robotic surgery and compares clinical morbidity and mortality outcomes of robotic versus open and robotic versus minimal access approaches across 99 randomised controlled trials. It provides a brief chronology of the history of robotic systems and summarises the available evidence to date across all platforms. The manuscript reports key outcomes such as blood loss, transfusion requirements, operative time, overall complications and length of stay. It also discusses the limitations of available trial data and the difficulties in collecting and summarising such comparative data.