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Cited by in CrossRef
For: Yoshida H, Kiyuna T. Requirements for implementation of artificial intelligence in the practice of gastrointestinal pathology. World J Gastroenterol 2021; 27(21): 2818-2833 [PMID: 34135556 DOI: 10.3748/wjg.v27.i21.2818]
URL: https://www.wjgnet.com/1007-9327/full/v27/i21/2818.htm
Number Citing Articles
1
Anil Alpsoy, Aysen Yavuz, Gulsum Ozlem Elpek. Artificial intelligence in pathological evaluation of gastrointestinal cancersArtificial Intelligence in Gastroenterology 2021; 2(6): 141-156 doi: 10.35712/aig.v2.i6.141
2
Surajit Bag, Pavitra Dhamija, Rajesh Kumar Singh, Muhammad Sabbir Rahman, V. Raja Sreedharan. Big data analytics and artificial intelligence technologies based collaborative platform empowering absorptive capacity in health care supply chain: An empirical studyJournal of Business Research 2023; 154: 113315 doi: 10.1016/j.jbusres.2022.113315
3
Yujin Oh, Go Eun Bae, Kyung-Hee Kim, Min-Kyung Yeo, Jong Chul Ye. Multi-Scale Hybrid Vision Transformer for Learning Gastric Histology: AI-Based Decision Support System for Gastric Cancer TreatmentIEEE Journal of Biomedical and Health Informatics 2023; 27(8): 4143 doi: 10.1109/JBHI.2023.3276778
4
Daniele Giansanti. The Regulation of Artificial Intelligence in Digital Radiology in the Scientific Literature: A Narrative Review of ReviewsHealthcare 2022; 10(10): 1824 doi: 10.3390/healthcare10101824
5
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
6
Saba Shafi, Anil V. Parwani. Artificial intelligence in diagnostic pathologyDiagnostic Pathology 2023; 18(1) doi: 10.1186/s13000-023-01375-z
7
Yujie Jing, Chen Li, Tianming Du, Tao Jiang, Hongzan Sun, Jinzhu Yang, Liyu Shi, Minghe Gao, Marcin Grzegorzek, Xiaoyan Li. A comprehensive survey of intestine histopathological image analysis using machine vision approachesComputers in Biology and Medicine 2023; 165: 107388 doi: 10.1016/j.compbiomed.2023.107388
8
David J Foran, Wenjin Chen, Tahsin Kurc, Rajarshi Gupta, Jakub Roman Kaczmarzyk, Luke Austin Torre-Healy, Erich Bremer, Samuel Ajjarapu, Nhan Do, Gerald Harris, Antoinette Stroup, Eric Durbin, Joel H Saltz. An Intelligent Search & Retrieval System (IRIS) and Clinical and Research Repository for Decision Support Based on Machine Learning and Joint Kernel-based Supervised HashingCancer Informatics 2024; 23 doi: 10.1177/11769351231223806
9
Corina-Elena Minciuna, Mihai Tanase, Teodora Ecaterina Manuc, Stefan Tudor, Vlad Herlea, Mihnea P. Dragomir, George A. Calin, Catalin Vasilescu. The seen and the unseen: Molecular classification and image based-analysis of gastrointestinal cancersComputational and Structural Biotechnology Journal 2022; 20: 5065 doi: 10.1016/j.csbj.2022.09.010
10
Albert Alhatem, Trish Wong, W. Clark Lambert. Revolutionizing Diagnostic Pathology: The Emergence and Impact of Artificial Intelligence- What Doesn't Kill You Makes You Stronger?Clinics in Dermatology 2024;  doi: 10.1016/j.clindermatol.2023.12.020
11
Shen Zhao, Chao-Yang Yan, Hong Lv, Jing-Cheng Yang, Chao You, Zi-Ang Li, Ding Ma, Yi Xiao, Jia Hu, Wen-Tao Yang, Yi-Zhou Jiang, Jun Xu, Zhi-Ming Shao. Deep learning framework for comprehensive molecular and prognostic stratifications of triple-negative breast cancerFundamental Research 2022;  doi: 10.1016/j.fmre.2022.06.008
12
Angelene Berwick, Graham Holland, Bradford Power, Amy Rebane, Breanne Butler, Nicolas M. Orsi. Patient and public involvement (PPI) in computer-aided diagnostics in digital histopathologyDiagnostic Histopathology 2023; 29(9): 410 doi: 10.1016/j.mpdhp.2023.06.008
13
Athena Davri, Effrosyni Birbas, Theofilos Kanavos, Georgios Ntritsos, Nikolaos Giannakeas, Alexandros T. Tzallas, Anna Batistatou. Deep Learning on Histopathological Images for Colorectal Cancer Diagnosis: A Systematic ReviewDiagnostics 2022; 12(4): 837 doi: 10.3390/diagnostics12040837
14
Joaquim Carreras. The pathobiology of follicular lymphomaJournal of Clinical and Experimental Hematopathology 2023; 63(3): 152 doi: 10.3960/jslrt.23014
15
Aysen Yavuz, Anil Alpsoy, Elif Ocak Gedik, Mennan Yigitcan Celik, Cumhur Ibrahim Bassorgun, Betul Unal, Gulsum Ozlem Elpek. Artificial intelligence applications in predicting the behavior of gastrointestinal cancers in pathologyArtificial Intelligence in Gastroenterology 2022; 3(5): 142-162 doi: 10.35712/aig.v3.i5.142
16
Tao Jin, Yancai Jiang, Boneng Mao, Xing Wang, Bo Lu, Ji Qian, Hutao Zhou, Tieliang Ma, Yefei Zhang, Sisi Li, Yun Shi, Zhendong Yao. Multi-center verification of the influence of data ratio of training sets on test results of an AI system for detecting early gastric cancer based on the YOLO-v4 algorithmFrontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.953090
17
Ali Azimi, Pablo Fernandez-Peñas. Molecular Classifiers in Skin Cancers: Challenges and PromisesCancers 2023; 15(18): 4463 doi: 10.3390/cancers15184463