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Cited by in F6Publishing
For: Watson MD, Baimas-George MR, Murphy KJ, Pickens RC, Iannitti DA, Martinie JB, Baker EH, Vrochides D, Ocuin LM. Pure and Hybrid Deep Learning Models can Predict Pathologic Tumor Response to Neoadjuvant Therapy in Pancreatic Adenocarcinoma: A Pilot Study. Am Surg 2020;:3134820982557. [PMID: 33381979 DOI: 10.1177/0003134820982557] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
Number Citing Articles
1 Barat M, Chassagnon G, Dohan A, Gaujoux S, Coriat R, Hoeffel C, Cassinotto C, Soyer P. Artificial intelligence: a critical review of current applications in pancreatic imaging. Jpn J Radiol 2021;39:514-23. [PMID: 33550513 DOI: 10.1007/s11604-021-01098-5] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
2 Hayashi H, Uemura N, Matsumura K, Zhao L, Sato H, Shiraishi Y, Yamashita YI, Baba H. Recent advances in artificial intelligence for pancreatic ductal adenocarcinoma. World J Gastroenterol 2021; 27(43): 7480-7496 [PMID: 34887644 DOI: 10.3748/wjg.v27.i43.7480] [Reference Citation Analysis]
3 Baimas-George M, Demartines N, Vrochides D. The role of disruptive technologies and approaches in ERAS®: erupting change through disruptive means. Langenbecks Arch Surg 2022. [PMID: 35083568 DOI: 10.1007/s00423-022-02450-7] [Reference Citation Analysis]