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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 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) doi: 10.1109/JBHI.2023.3276778
4
Mario Alejandro García, Martín Nicolás Gramática, Juan Pablo Ricapito. Intermediate Task Fine-Tuning in Cancer ClassificationJournal of Computer Science and Technology 2023; 23(2) doi: 10.24215/16666038.23.e12
5
Agnieszka Pilch, Ryszard Zygała, Wiesława Gryncewicz, Mykola Dyvak, Andriy Melnyk. Emerging Challenges in Intelligent Management Information SystemsLecture Notes in Networks and Systems 2024; 1079 doi: 10.1007/978-3-031-66761-9_6
6
Muhammed Mubarak, Rahma Rashid, Fnu Sapna, Shaheera Shakeel. Expanding role and scope of artificial intelligence in the field of gastrointestinal pathologyArtificial Intelligence in Gastroenterology 2024; 5(2): 91550 doi: 10.35712/aig.v5.i2.91550
7
Tomoharu Kiyuna, Eric Cosatto, Kanako C. Hatanaka, Tomoyuki Yokose, Koji Tsuta, Noriko Motoi, Keishi Makita, Ai Shimizu, Toshiya Shinohara, Akira Suzuki, Emi Takakuwa, Yasunari Takakuwa, Takahiro Tsuji, Mitsuhiro Tsujiwaki, Mitsuru Yanai, Sayaka Yuzawa, Maki Ogura, Yutaka Hatanaka. Evaluating Cellularity Estimation Methods: Comparing AI Counting with Pathologists’ Visual EstimatesDiagnostics 2024; 14(11) doi: 10.3390/diagnostics14111115
8
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 doi: 10.1016/j.csbj.2022.09.010
9
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) doi: 10.1016/j.mpdhp.2023.06.008
10
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) doi: 10.3390/diagnostics12040837
11
Joaquim Carreras. The pathobiology of follicular lymphomaJournal of Clinical and Experimental Hematopathology 2023; 63(3) doi: 10.3960/jslrt.23014
12
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
13
Ali Azimi, Pablo Fernandez-Peñas. Molecular Classifiers in Skin Cancers: Challenges and PromisesCancers 2023; 15(18) doi: 10.3390/cancers15184463
14
Liucheng Li, Fang Lv, Chen Du, Lianjun Yang, Chengzhou Pa, Yunrui Dai. Artificial intelligence-driven gastrointestinal functional assessment: multimodal imaging, digital biomarkers, and real-time monitoringFrontiers in Physiology 2026; 17 doi: 10.3389/fphys.2026.1778235
15
Daniele Giansanti. The Regulation of Artificial Intelligence in Digital Radiology in the Scientific Literature: A Narrative Review of ReviewsHealthcare 2022; 10(10) doi: 10.3390/healthcare10101824
16
Saba Shafi, Anil V. Parwani. Artificial intelligence in diagnostic pathologyDiagnostic Pathology 2023; 18(1) doi: 10.1186/s13000-023-01375-z
17
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 doi: 10.1016/j.compbiomed.2023.107388
18
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
19
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; 42(3) doi: 10.1016/j.clindermatol.2023.12.020
20
Yee Lin Tang, Daniel Dahlmeier. A Review on the Logistics, Financial, Ethical, and Regulatory Frameworks of Artificial Intelligence in Digital PathologyAPMIS 2026; 134(6) doi: 10.1111/apm.70227
21
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 2024; 4(3) doi: 10.1016/j.fmre.2022.06.008
22
Moutaz W Sweileh. AI-Powered histopathology slide image interpretation in oncology: A comprehensive knowledge mapping and bibliometric analysisDIGITAL HEALTH 2025; 11 doi: 10.1177/20552076251393286
23
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
24
Marianne Remke, Tanja Groll, Thomas Metzler, Elisabeth Urbauer, Janine Kövilein, Theresa Schnalzger, Jürgen Ruland, Dirk Haller, Katja Steiger. Histomorphological scoring of murine colitis models: A practical guide for the evaluation of colitis and colitis-associated cancerExperimental and Molecular Pathology 2024; 140 doi: 10.1016/j.yexmp.2024.104938
25
M. M. Kolotilov, V. V. Solodushchenko, B. A. Tarasyuk, V. S. Berezenko. Artificial intelligence and radiological diagnostics in hepatologyThe Ukrainian Journal of Clinical Surgery 2025; 92(3) doi: 10.26779/2786-832X.2025.3.62
26
Mohammad Haseeb, Md. Mominur Rahman, Mustafa Kamal, Sachin Ghai, Neeru Sidana. AI-Driven Environmental Pollution ManagementClimate Risks and Solutions 2025;  doi: 10.1007/978-3-031-96243-1_12