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Cited by in CrossRef
For: Shao SL, Li YK, Qin JC, Liu L. Comprehensive abdominal composition evaluation of rectal cancer patients with anastomotic leakage compared with body mass index-matched controls. World J Gastrointest Surg 2022; 14(11): 1250-1259 [PMID: 36504512 DOI: 10.4240/wjgs.v14.i11.1250]
URL: https://www.wjgnet.com/1948-9366/full/v14/i11/1250.htm
Number Citing Articles
1
Mark Broekman, Charlotte M. S. Genders, Ritchie T. J. Geitenbeek, Klaas Havenga, Schelto Kruijff, Joost M. Klaase, Alain R. Viddeleer, Esther C. J. Consten, Ozlem Boybeyi-Turer. Unraveling the role of computed tomography derived body composition metrics on anastomotic leakages rates in rectal cancer surgery: A protocol for a systematic review and meta-analysisPLOS ONE 2024; 19(7) doi: 10.1371/journal.pone.0307606
2
Dorsa Salabat, Asma Mousavi, Shayan Shojaei, Razman Arabzadeh Bahri, Hanieh Radkhah. Preoperative body composition metrics as predictors for outcomes in colorectal cancer surgeriesAnnals of Medicine & Surgery 2025; 87(4) doi: 10.1097/MS9.0000000000003059
3
Andrew A Gumbs, Gaya Spolverato, Giulia Capelli, Quoc R Bao, Francesco Celotto. Machine learning and deep learning to improve prevention of anastomotic leak after rectal cancer surgeryWorld Journal of Gastrointestinal Surgery 2025; 17(1): 101772 doi: 10.4240/wjgs.v17.i1.101772
4
Mark Broekman, Charlotte M.S. Genders, Ritchie T.J. Geitenbeek, Klaas Havenga, Schelto Kruijff, Joost M. Klaase, Alain R. Viddeleer, Jeroen L.A. van Vugt, Esther C.J. Consten. Computed tomography derived body composition and risk of anastomotic leakage following rectal cancer surgery: A systematic review and meta-analysisClinical Nutrition ESPEN 2026; 75 doi: 10.1016/j.clnesp.2026.103417
5
Francesco Celotto, Giulia Capelli, Stefania Ferrari, Marco Scarpa, Salvatore Pucciarelli, Gaya Spolverato. Application and use of artificial intelligence in colorectal cancer surgery: where are we?Artificial Intelligence Surgery 2024; 4(4) doi: 10.20517/ais.2024.26