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Cited by in F6Publishing
For: Sala Elarre P, Oyaga-Iriarte E, Yu KH, Baudin V, Arbea Moreno L, Carranza O, Chopitea Ortega A, Ponz-Sarvise M, Mejías Sosa LD, Rotellar Sastre F, Larrea Leoz B, Iragorri Barberena Y, Subtil Iñigo JC, Benito Boíllos A, Pardo F, Rodríguez Rodríguez J. Use of Machine-Learning Algorithms in Intensified Preoperative Therapy of Pancreatic Cancer to Predict Individual Risk of Relapse. Cancers (Basel) 2019;11:E606. [PMID: 31052270 DOI: 10.3390/cancers11050606] [Cited by in Crossref: 7] [Cited by in F6Publishing: 5] [Article Influence: 3.5] [Reference Citation Analysis]
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2 Mandrell CT, Holland TE, Wheeler JF, Esmaeili SMA, Amar K, Chowdhury F, Sivakumar P. Machine Learning Approach to Raman Spectrum Analysis of MIA PaCa-2 Pancreatic Cancer Tumor Repopulating Cells for Classification and Feature Analysis. Life (Basel). 2020;10. [PMID: 32899572 DOI: 10.3390/life10090181] [Cited by in Crossref: 3] [Article Influence: 3.0] [Reference Citation Analysis]
3 Bari H, Wadhwani S, Dasari BVM. Role of artificial intelligence in hepatobiliary and pancreatic surgery. World J Gastrointest Surg 2021;13:7-18. [PMID: 33552391 DOI: 10.4240/wjgs.v13.i1.7] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
4 Mendoza Ladd A, Diehl DL. Artificial intelligence for early detection of pancreatic adenocarcinoma: The future is promising. World J Gastroenterol 2021;27:1283-95. [PMID: 33833482 DOI: 10.3748/wjg.v27.i13.1283] [Reference Citation Analysis]
5 Li X, Yang L, Yuan Z, Lou J, Fan Y, Shi A, Huang J, Zhao M, Wu Y. Multi-institutional development and external validation of machine learning-based models to predict relapse risk of pancreatic ductal adenocarcinoma after radical resection. J Transl Med 2021;19:281. [PMID: 34193166 DOI: 10.1186/s12967-021-02955-7] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]