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: PMC8173389 DOI: 10.3748/wjg.v27.i21.2818] |
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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 cancers. Artificial Intelligence in Gastroenterology 2021; 2(6): 141-156 doi: 10.35712/aig.v2.i6.141
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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 study. Journal of Business Research 2023; 154: 113315 doi: 10.1016/j.jbusres.2022.113315
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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 Treatment. IEEE Journal of Biomedical and Health Informatics 2023; 27(8): 4143 doi: 10.1109/JBHI.2023.3276778
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Daniele Giansanti. The Regulation of Artificial Intelligence in Digital Radiology in the Scientific Literature: A Narrative Review of Reviews. Healthcare 2022; 10(10): 1824 doi: 10.3390/healthcare10101824
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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): e12 doi: 10.24215/16666038.23.e12
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Agnieszka Pilch, Ryszard Zygała, Wiesława Gryncewicz, Mykola Dyvak, Andriy Melnyk. Emerging Challenges in Intelligent Management Information Systems. Lecture Notes in Networks and Systems 2024; 1079: 62 doi: 10.1007/978-3-031-66761-9_6
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7 |
Muhammed Mubarak, Rahma Rashid, Fnu Sapna, Shaheera Shakeel. Expanding role and scope of artificial intelligence in the field of gastrointestinal pathology. Artificial Intelligence in Gastroenterology 2024; 5(2): 91550 doi: 10.35712/aig.v5.i2.91550
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8 |
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 Estimates. Diagnostics 2024; 14(11): 1115 doi: 10.3390/diagnostics14111115
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Saba Shafi, Anil V. Parwani. Artificial intelligence in diagnostic pathology. Diagnostic Pathology 2023; 18(1) doi: 10.1186/s13000-023-01375-z
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10 |
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 approaches. Computers in Biology and Medicine 2023; 165: 107388 doi: 10.1016/j.compbiomed.2023.107388
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11 |
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 Hashing. Cancer Informatics 2024; 23 doi: 10.1177/11769351231223806
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12 |
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 cancers. Computational and Structural Biotechnology Journal 2022; 20: 5065 doi: 10.1016/j.csbj.2022.09.010
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13 |
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): 268 doi: 10.1016/j.clindermatol.2023.12.020
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14 |
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 cancer. Fundamental Research 2024; 4(3): 678 doi: 10.1016/j.fmre.2022.06.008
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15 |
Angelene Berwick, Graham Holland, Bradford Power, Amy Rebane, Breanne Butler, Nicolas M. Orsi. Patient and public involvement (PPI) in computer-aided diagnostics in digital histopathology. Diagnostic Histopathology 2023; 29(9): 410 doi: 10.1016/j.mpdhp.2023.06.008
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16 |
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 Review. Diagnostics 2022; 12(4): 837 doi: 10.3390/diagnostics12040837
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17 |
Joaquim Carreras. The pathobiology of follicular lymphoma. Journal of Clinical and Experimental Hematopathology 2023; 63(3): 152 doi: 10.3960/jslrt.23014
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18 |
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 pathology. Artificial Intelligence in Gastroenterology 2022; 3(5): 142-162 doi: 10.35712/aig.v3.i5.142
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