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Cited by in CrossRef
For: Kobayashi S, Saltz JH, Yang VW. State of machine and deep learning in histopathological applications in digestive diseases. World J Gastroenterol 2021; 27(20): 2545-2575 [PMID: 34092975 DOI: 10.3748/wjg.v27.i20.2545]
URL: https://www.wjgnet.com/1007-9327/full/v27/i20/2545.htm
Number Citing Articles
1
Ksenia S. Maslyonkina, Alexandra K. Konyukova, Darya Y. Alexeeva, Mikhail Y. Sinelnikov, Liudmila M. Mikhaleva. Barrett's esophagus: The pathomorphological and molecular genetic keystones of neoplastic progressionCancer Medicine 2022; 11(2): 447 doi: 10.1002/cam4.4447
2
Lijuan Feng, Luodan Qian, Shen Yang, Qinghua Ren, Shuxin Zhang, Hong Qin, Wei Wang, Chao Wang, Hui Zhang, Jigang Yang. Prediction for Mitosis-Karyorrhexis Index Status of Pediatric Neuroblastoma via Machine Learning Based 18F-FDG PET/CT RadiomicsDiagnostics 2022; 12(2): 262 doi: 10.3390/diagnostics12020262
3
Biljana Stankovic, Nikola Kotur, Gordana Nikcevic, Vladimir Gasic, Branka Zukic, Sonja Pavlovic. Machine Learning Modeling from Omics Data as Prospective Tool for Improvement of Inflammatory Bowel Disease Diagnosis and Clinical ClassificationsGenes 2021; 12(9): 1438 doi: 10.3390/genes12091438
4
Daniel D. Penrice, Puru Rattan, Douglas A. Simonetto. Artificial Intelligence and the Future of Gastroenterology and HepatologyGastro Hep Advances 2022; 1(4): 581 doi: 10.1016/j.gastha.2022.02.025