TY - JOUR
T1 - The integration of artificial intelligence in robotic surgery
T2 - A narrative review
AU - Zhang, Chi
AU - Hallbeck, M. Susan
AU - Salehinejad, Hojjat
AU - Thiels, Cornelius
N1 - Publisher Copyright:
© 2024 Elsevier Inc.
PY - 2024
Y1 - 2024
N2 - Background: The rise of high-definition imaging and robotic surgery has independently been associated with improved postoperative outcomes. However, steep learning curves and finite human cognitive ability limit the facility in imaging interpretation and interaction with the robotic surgery console interfaces. This review presents innovative ways in which artificial intelligence integrates preoperative imaging and surgery to help overcome these limitations and to further advance robotic operations. Methods: PubMed was queried for “artificial intelligence,” “machine learning,” and “robotic surgery.” From the 182 publications in English, a further in-depth review of the cited literature was performed. Results: Artificial intelligence boasts efficiency and proclivity for large amounts of unwieldy and unstructured data. Its wide adoption has significant practice-changing implications throughout the perioperative period. Assessment of preoperative imaging can augment preoperative surgeon knowledge by accessing pathology data that have been traditionally only available postoperatively through analysis of preoperative imaging. Intraoperatively, the interaction of artificial intelligence with augmented reality through the dynamic overlay of preoperative anatomical knowledge atop the robotic operative field can outline safe dissection planes, helping surgeons make critical real-time intraoperative decisions. Finally, semi-independent artificial intelligence–assisted robotic operations may one day be performed by artificial intelligence with limited human intervention. Conclusion: As artificial intelligence has allowed machines to think and problem-solve like humans, it promises further advancement of existing technologies and a revolution of individualized patient care. Further research and ethical precautions are necessary before the full implementation of artificial intelligence in robotic surgery.
AB - Background: The rise of high-definition imaging and robotic surgery has independently been associated with improved postoperative outcomes. However, steep learning curves and finite human cognitive ability limit the facility in imaging interpretation and interaction with the robotic surgery console interfaces. This review presents innovative ways in which artificial intelligence integrates preoperative imaging and surgery to help overcome these limitations and to further advance robotic operations. Methods: PubMed was queried for “artificial intelligence,” “machine learning,” and “robotic surgery.” From the 182 publications in English, a further in-depth review of the cited literature was performed. Results: Artificial intelligence boasts efficiency and proclivity for large amounts of unwieldy and unstructured data. Its wide adoption has significant practice-changing implications throughout the perioperative period. Assessment of preoperative imaging can augment preoperative surgeon knowledge by accessing pathology data that have been traditionally only available postoperatively through analysis of preoperative imaging. Intraoperatively, the interaction of artificial intelligence with augmented reality through the dynamic overlay of preoperative anatomical knowledge atop the robotic operative field can outline safe dissection planes, helping surgeons make critical real-time intraoperative decisions. Finally, semi-independent artificial intelligence–assisted robotic operations may one day be performed by artificial intelligence with limited human intervention. Conclusion: As artificial intelligence has allowed machines to think and problem-solve like humans, it promises further advancement of existing technologies and a revolution of individualized patient care. Further research and ethical precautions are necessary before the full implementation of artificial intelligence in robotic surgery.
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U2 - 10.1016/j.surg.2024.02.005
DO - 10.1016/j.surg.2024.02.005
M3 - Review article
AN - SCOPUS:85187689055
SN - 0039-6060
JO - Surgery (United States)
JF - Surgery (United States)
ER -