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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/2307-8960/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
Bo-Jhang Lin, Tien-Chueh Kuo, Hsin-Hsiang Chung, Ying-Chen Huang, Ming-Yang Wang, Cheng-Chih Hsu, Po-Yang Yao, Yufeng Jane Tseng. MSIr: Automatic Registration Service for Mass Spectrometry Imaging and HistologyAnalytical Chemistry 2023; 95(6): 3317 doi: 10.1021/acs.analchem.2c04360
3
Mario Alejandro García, Martín Nicolás Gramática, Juan Pablo Ricapito. Intermediate Task Fine-Tuning in Cancer ClassificationJournal of Computer Science and Technology 2023; 23(2): e12 doi: 10.24215/16666038.23.e12
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
5
Qing Li, Shan Geng, Hao Luo, Wei Wang, Ya-Qi Mo, Qing Luo, Lu Wang, Guan-Bin Song, Jian-Peng Sheng, Bo Xu. Signaling pathways involved in colorectal cancer: pathogenesis and targeted therapySignal Transduction and Targeted Therapy 2024; 9(1) doi: 10.1038/s41392-024-01953-7
6
Manuel A. Chablé-Vega, Eleazar García-Hernández, Jorge E. Martínez-Heredia, José L. Villalpando-Aguilar, Jesús Arreola-Enríquez, Itzel López-Rosas, Fulgencio Alatorre-Cobos. The return of natural dyes: the case of logwood tree ( Haematoxylum campechianum L.) Biotechnic & Histochemistry 2024; : 1 doi: 10.1080/10520295.2024.2367535
7
José Guilherme de Almeida, Emma Gudgin, Martin Besser, William G. Dunn, Jonathan Cooper, Torsten Haferlach, George S. Vassiliou, Moritz Gerstung. Computational analysis of peripheral blood smears detects disease-associated cytomorphologiesNature Communications 2023; 14(1) doi: 10.1038/s41467-023-39676-y
8
Cuiqing Bai, Yan Sun, Xiuqin Zhang, Zhitong Zuo. Assessment of AURKA expression and prognosis prediction in lung adenocarcinoma using machine learning-based pathomics signatureHeliyon 2024; 10(12): e33107 doi: 10.1016/j.heliyon.2024.e33107
9
Lingfeng Zhu, Jindong Liu, Dongmei Zheng, Ziran Cao, Fei Miao, Cheng Li, Jian He, Jing Guo. An Intestinal Tumors Detection Model Based on Feature Distillation With Self-Correction Mechanism and PathGANIEEE Access 2024; 12: 51676 doi: 10.1109/ACCESS.2024.3380910
10
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
11
Soma Kobayashi, Jason Shieh, Ainara Ruiz de Sabando, Julie Kim, Yang Liu, Sui Y. Zee, Prateek Prasanna, Agnieszka B. Bialkowska, Joel H. Saltz, Vincent W. Yang, Sripathi M. Sureban. Deep learning-based approach to the characterization and quantification of histopathology in mouse models of colitisPLOS ONE 2022; 17(8): e0268954 doi: 10.1371/journal.pone.0268954
12
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
13
Wenbin He, Ting Liu, Yongjie Han, Wuyi Ming, Jinguang Du, Yinxia Liu, Yuan Yang, Leijie Wang, Zhiwen Jiang, Yongqiang Wang, Jie Yuan, Chen Cao. A review: The detection of cancer cells in histopathology based on machine visionComputers in Biology and Medicine 2022; 146: 105636 doi: 10.1016/j.compbiomed.2022.105636