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Cited by in CrossRef
For: Berbís MA, Aneiros-Fernández J, Mendoza Olivares FJ, Nava E, Luna A. Role of artificial intelligence in multidisciplinary imaging diagnosis of gastrointestinal diseases. World J Gastroenterol 2021; 27(27): 4395-4412 [PMID: 34366612 DOI: 10.3748/wjg.v27.i27.4395]
URL: https://www.wjgnet.com/1007-9327/full/v27/i27/4395.htm
Number Citing Articles
1
M Alvaro Berbís, Felix Paulano Godino, Javier Royuela del Val, Lidia Alcalá Mata, Antonio Luna. Clinical impact of artificial intelligence-based solutions on imaging of the pancreas and liverWorld Journal of Gastroenterology 2023; 29(9): 1427-1445 doi: 10.3748/wjg.v29.i9.1427
2
Zuzanna Pelc, Katarzyna Sędłak, Magdalena Leśniewska, Katarzyna Mielniczek, Katarzyna Chawrylak, Magdalena Skórzewska, Tomasz Ciszewski, Joanna Czechowska, Agata Kiszczyńska, Bas P. L. Wijnhoven, Johanna W. Van Sandick, Ines Gockel, Suzanne S. Gisbertz, Guillaume Piessen, Clarisse Eveno, Maria Bencivenga, Giovanni De Manzoni, Gian Luca Baiocchi, Paolo Morgagni, Riccardo Rosati, Uberto Fumagalli Romario, Andrew Davies, Yutaka Endo, Timothy M. Pawlik, Franco Roviello, Christiane Bruns, Wojciech P. Polkowski, Karol Rawicz-Pruszyński. Textbook Neoadjuvant Outcome—Novel Composite Measure of Oncological Outcomes among Gastric Cancer Patients Undergoing Multimodal TreatmentCancers 2024; 16(9): 1721 doi: 10.3390/cancers16091721
3
洪铭 崔. Application of Artificial Intelligence in Gastrointestinal CancerAdvances in Clinical Medicine 2023; 13(03): 3942 doi: 10.12677/ACM.2023.133566
4
Jirui Guo, Wuteng Cao, Bairun Nie, Qiyuan Qin. Unsupervised Learning Composite Network to Reduce Training Cost of Deep Learning Model for Colorectal Cancer DiagnosisIEEE Journal of Translational Engineering in Health and Medicine 2023; 11: 54 doi: 10.1109/JTEHM.2022.3224021
5
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
6
Binglan Zhang, Fuping Zhu, Pan Li, Jing Zhu. Artificial intelligence-assisted endoscopic ultrasound in the diagnosis of gastrointestinal stromal tumors: a meta-analysisSurgical Endoscopy 2023; 37(3): 1649 doi: 10.1007/s00464-022-09597-w
7
Sara Massironi. Advancements in Barrett's esophagus detection: The role of artificial intelligence and its implicationsWorld Journal of Gastroenterology 2024; 30(11): 1494-1496 doi: 10.3748/wjg.v30.i11.1494
8
Aaron R Brenner, Passisd Laoveeravat, Patrick J Carey, Danielle Joiner, Samuel H Mardini, Manol Jovani. Artificial intelligence using advanced imaging techniques and cholangiocarcinoma: Recent advances and future directionArtificial Intelligence in Gastroenterology 2022; 3(3): 88-95 doi: 10.35712/aig.v3.i3.88
9
Sang-Hyun Kim, Hyuk-Soon Choi, Bora Keum, Hoon-Jai Chun. Robotics in Gastrointestinal EndoscopyApplied Sciences 2021; 11(23): 11351 doi: 10.3390/app112311351
10
Madalina Stan-Ilie, Vasile Sandru, Gabriel Constantinescu, Oana-Mihaela Plotogea, Ecaterina Mihaela Rinja, Iulia Florentina Tincu, Alexandra Jichitu, Adriana Elena Carasel, Andreea Cristina Butuc, Bogdan Popa. Artificial Intelligence—The Rising Star in the Field of Gastroenterology and HepatologyDiagnostics 2023; 13(4): 662 doi: 10.3390/diagnostics13040662
11
M. Haripriyaa, K. Suthindhiran, M.A. Jayasri. Human and Animal Microbiome Engineering2025; : 179 doi: 10.1016/B978-0-443-22348-8.00010-6
12
Muhammed Yaman Swied, Bader Abou Shaar, Nabel Rajab Basha. Exploring the Current Role of Deep Learning in Radiologic Imaging of Gastrointestinal DiseasesInnovations in Digital Health, Diagnostics, and Biomarkers 2024; 4(2024): 68 doi: 10.36401/IDDB-24-1