TY - JOUR
T1 - Artificial intelligence in colorectal surgery
T2 - an AI-powered systematic review
AU - Spinelli, A.
AU - Carrano, F. M.
AU - Laino, M. E.
AU - Andreozzi, M.
AU - Koleth, G.
AU - Hassan, C.
AU - Repici, A.
AU - Chand, M.
AU - Savevski, V.
AU - Pellino, G.
N1 - © 2023. Springer Nature Switzerland AG.
PY - 2023/2/21
Y1 - 2023/2/21
N2 - Artificial intelligence (AI) has the potential to revolutionize surgery in the coming years. Still, it is essential to clarify what the meaningful current applications are and what can be reasonably expected. This AI-powered review assessed the role of AI in colorectal surgery. A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-compliant systematic search of PubMed, Embase, Scopus, Cochrane Library databases, and gray literature was conducted on all available articles on AI in colorectal surgery (from January 1 1997 to March 1 2021), aiming to define the perioperative applications of AI. Potentially eligible studies were identified using novel software powered by natural language processing (NLP) and machine learning (ML) technologies dedicated to systematic reviews. Out of 1238 articles identified, 115 were included in the final analysis. Available articles addressed the role of AI in several areas of interest. In the preoperative phase, AI can be used to define tailored treatment algorithms, support clinical decision-making, assess the risk of complications, and predict surgical outcomes and survival. Intraoperatively, AI-enhanced surgery and integration of AI in robotic platforms have been suggested. After surgery, AI can be implemented in the Enhanced Recovery after Surgery (ERAS) pathway. Additional areas of applications included the assessment of patient-reported outcomes, automated pathology assessment, and research. Available data on these aspects are limited, and AI in colorectal surgery is still in its infancy. However, the rapid evolution of technologies makes it likely that it will increasingly be incorporated into everyday practice.
AB - Artificial intelligence (AI) has the potential to revolutionize surgery in the coming years. Still, it is essential to clarify what the meaningful current applications are and what can be reasonably expected. This AI-powered review assessed the role of AI in colorectal surgery. A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-compliant systematic search of PubMed, Embase, Scopus, Cochrane Library databases, and gray literature was conducted on all available articles on AI in colorectal surgery (from January 1 1997 to March 1 2021), aiming to define the perioperative applications of AI. Potentially eligible studies were identified using novel software powered by natural language processing (NLP) and machine learning (ML) technologies dedicated to systematic reviews. Out of 1238 articles identified, 115 were included in the final analysis. Available articles addressed the role of AI in several areas of interest. In the preoperative phase, AI can be used to define tailored treatment algorithms, support clinical decision-making, assess the risk of complications, and predict surgical outcomes and survival. Intraoperatively, AI-enhanced surgery and integration of AI in robotic platforms have been suggested. After surgery, AI can be implemented in the Enhanced Recovery after Surgery (ERAS) pathway. Additional areas of applications included the assessment of patient-reported outcomes, automated pathology assessment, and research. Available data on these aspects are limited, and AI in colorectal surgery is still in its infancy. However, the rapid evolution of technologies makes it likely that it will increasingly be incorporated into everyday practice.
KW - Ai
KW - Artificial intelligence
KW - Colorectal
KW - Machine learning
KW - Radiomics
KW - Risk assessment
KW - Surgery
UR - http://www.scopus.com/inward/record.url?scp=85148462262&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/b0c0f52f-b5e4-382c-8153-41ebd5f639e7/
UR - https://portalrecerca.uab.cat/en/publications/f909a8e9-d23e-4f7f-a3c1-968180e28d6f
U2 - 10.1007/s10151-023-02772-8
DO - 10.1007/s10151-023-02772-8
M3 - Review article
C2 - 36805890
AN - SCOPUS:85148462262
SN - 1123-6337
VL - 27
SP - 615
EP - 629
JO - Techniques in Coloproctology
JF - Techniques in Coloproctology
IS - 8
ER -