| 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] |
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| URL: | https://www.wjgnet.com/1007-9327/full/v27/i20/2545.htm |
| Number | Citing Articles |
| 1 |
Vishesh Tanwar, Bhisham Sharma, Dhirendra Prasad Yadav, Abolfazl Mehbodniya. Hybrid deep learning framework based on EfficientViT for classification of gastrointestinal diseases. Scientific Reports 2025; 15(1) doi: 10.1038/s41598-025-12128-x
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| 2 |
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 progression. Cancer Medicine 2022; 11(2) doi: 10.1002/cam4.4447
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| 3 |
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 Histology. Analytical Chemistry 2023; 95(6) doi: 10.1021/acs.analchem.2c04360
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| 4 |
Mario Alejandro García, Martín Nicolás Gramática, Juan Pablo Ricapito. Intermediate Task Fine-Tuning in Cancer Classification. Journal of Computer Science and Technology 2023; 23(2) doi: 10.24215/16666038.23.e12
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| 5 |
Margherita Mottola, Costantino Ricci, Federico Chiarucci, Caterina Ravaioli, Alessia Grillini, Alessandro Gherardi, Michelangelo Fiorentino, Alessandro Bevilacqua, Francesca Ambrosi. Computer-Based Detection of Colorectal Serrated Lesions: Digital Flatness, a Novel Metric Designed for Whole-Slide Images. Laboratory Investigation 2025; 105(8) doi: 10.1016/j.labinv.2025.104178
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| 6 |
Daniel D. Penrice, Puru Rattan, Douglas A. Simonetto. Artificial Intelligence and the Future of Gastroenterology and Hepatology. Gastro Hep Advances 2022; 1(4) doi: 10.1016/j.gastha.2022.02.025
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| 7 |
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 therapy. Signal Transduction and Targeted Therapy 2024; 9(1) doi: 10.1038/s41392-024-01953-7
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| 8 |
Marjan Talebi, Negar Bozorgchami, Gauransh Mishra, Gaurav Mishra, Rouzbeh Almasi Ghale. Clinical validation of artificial intelligence for gastrointestinal diseases. Informatics in Medicine Unlocked 2026; 61 doi: 10.1016/j.imu.2026.101736
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| 9 |
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; 99(5) doi: 10.1080/10520295.2024.2367535
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| 10 |
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 cytomorphologies. Nature Communications 2023; 14(1) doi: 10.1038/s41467-023-39676-y
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| 11 |
Cuiqing Bai, Yan Sun, Xiuqin Zhang, Zhitong Zuo. Assessment of AURKA expression and prognosis prediction in lung adenocarcinoma using machine learning-based pathomics signature. Heliyon 2024; 10(12) doi: 10.1016/j.heliyon.2024.e33107
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| 12 |
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 PathGAN. IEEE Access 2024; 12 doi: 10.1109/ACCESS.2024.3380910
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| 13 |
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 Radiomics. Diagnostics 2022; 12(2) doi: 10.3390/diagnostics12020262
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| 14 |
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 colitis. PLOS ONE 2022; 17(8) doi: 10.1371/journal.pone.0268954
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| 15 |
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 Classifications. Genes 2021; 12(9) doi: 10.3390/genes12091438
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| 16 |
Pranay Wal, Jyotsana Dwivedi, Kanika Pandey, Krishana Kumar Sharma, Mohit Tiwari, Md Sajid Ali, Abida Khan, Amin Gasmi. Advances in artificial intelligence for predictive toxicology: From QSAR and omics integration to clinical safety translation. Computational Biology and Chemistry 2026; 124 doi: 10.1016/j.compbiolchem.2026.109120
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| 17 |
Cecilie Brandt Becker, Mette Sif Hansen, Søren Saxmose Nielsen, Henrik Elvang Jensen. Machine-learning for quantitative histopathology of piglet intestinal tissues: challenges with limited training data. Frontiers in Veterinary Science 2025; 12 doi: 10.3389/fvets.2025.1620338
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| 18 |
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 vision. Computers in Biology and Medicine 2022; 146 doi: 10.1016/j.compbiomed.2022.105636
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