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For: Kaissis GA, Ziegelmayer S, Lohöfer FK, Harder FN, Jungmann F, Sasse D, Muckenhuber A, Yen HY, Steiger K, Siveke J, Friess H, Schmid R, Weichert W, Makowski MR, Braren RF. Image-Based Molecular Phenotyping of Pancreatic Ductal Adenocarcinoma. J Clin Med 2020;9:E724. [PMID: 32155990 DOI: 10.3390/jcm9030724] [Cited by in Crossref: 13] [Cited by in F6Publishing: 10] [Article Influence: 13.0] [Reference Citation Analysis]
Number Citing Articles
1 Gutiérrez ML, Muñoz-Bellvís L, Orfao A. Genomic Heterogeneity of Pancreatic Ductal Adenocarcinoma and Its Clinical Impact. Cancers (Basel) 2021;13:4451. [PMID: 34503261 DOI: 10.3390/cancers13174451] [Reference Citation Analysis]
2 Jungmann F, Kaissis GA, Ziegelmayer S, Harder F, Schilling C, Yen HY, Steiger K, Weichert W, Schirren R, Demir IE, Friess H, Makowski MR, Braren RF, Lohöfer FK. Prediction of Tumor Cellularity in Resectable PDAC from Preoperative Computed Tomography Imaging. Cancers (Basel) 2021;13:2069. [PMID: 33922981 DOI: 10.3390/cancers13092069] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
3 Zha HL, Zong M, Liu XP, Pan JZ, Wang H, Gong HY, Xia TS, Liu XA, Li CY. Preoperative ultrasound-based radiomics score can improve the accuracy of the Memorial Sloan Kettering Cancer Center nomogram for predicting sentinel lymph node metastasis in breast cancer. Eur J Radiol 2021;135:109512. [PMID: 33429302 DOI: 10.1016/j.ejrad.2020.109512] [Reference Citation Analysis]
4 Wang S, Zheng Y, Yang F, Zhu L, Zhu XQ, Wang ZF, Wu XL, Zhou CH, Yan JY, Hu BY, Kong B, Fu DL, Bruns C, Zhao Y, Qin LX, Dong QZ. The molecular biology of pancreatic adenocarcinoma: translational challenges and clinical perspectives. Signal Transduct Target Ther 2021;6:249. [PMID: 34219130 DOI: 10.1038/s41392-021-00659-4] [Reference Citation Analysis]
5 Xie XJ, Liu SY, Chen JY, Zhao Y, Jiang J, Wu L, Zhang XW, Wu Y, Duan H, He B, Luo H, Han D. Development of unenhanced CT-based imaging signature for BAP1 mutation status prediction in malignant pleural mesothelioma: Consideration of 2D and 3D segmentation. Lung Cancer 2021;157:30-9. [PMID: 34052706 DOI: 10.1016/j.lungcan.2021.04.023] [Reference Citation Analysis]
6 Gorris M, Hoogenboom SA, Wallace MB, van Hooft JE. Artificial intelligence for the management of pancreatic diseases. Dig Endosc 2021;33:231-41. [PMID: 33065754 DOI: 10.1111/den.13875] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
7 Laoveeravat P, Abhyankar PR, Brenner AR, Gabr MM, Habr FG, Atsawarungruangkit A. Artificial intelligence for pancreatic cancer detection: Recent development and future direction . Artif Intell Gastroenterol 2021; 2(2): 56-68 [DOI: 10.35712/aig.v2.i2.56] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
8 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 [DOI: 10.3748/wjg.v27.i43.7480] [Reference Citation Analysis]
9 Kröner PT, Engels MM, Glicksberg BS, Johnson KW, Mzaik O, van Hooft JE, Wallace MB, El-Serag HB, Krittanawong C. Artificial intelligence in gastroenterology: A state-of-the-art review. World J Gastroenterol 2021; 27(40): 6794-6824 [DOI: 10.3748/wjg.v27.i40.6794] [Reference Citation Analysis]
10 Kaissis GA, Jungmann F, Ziegelmayer S, Lohöfer FK, Harder FN, Schlitter AM, Muckenhuber A, Steiger K, Schirren R, Friess H, Schmid R, Weichert W, Makowski MR, Braren RF. Multiparametric Modelling of Survival in Pancreatic Ductal Adenocarcinoma Using Clinical, Histomorphological, Genetic and Image-Derived Parameters. J Clin Med 2020;9:E1250. [PMID: 32344944 DOI: 10.3390/jcm9051250] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 3.0] [Reference Citation Analysis]