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Cited by in CrossRef
For: Tsai MC, Yen HH, Tsai HY, Huang YK, Luo YS, Kornelius E, Sung WW, Lin CC, Tseng MH, Wang CC. Artificial intelligence system for the detection of Barrett’s esophagus. World J Gastroenterol 2023; 29(48): 6198-6207 [PMID: 38186865 DOI: 10.3748/wjg.v29.i48.6198]
URL: https://www.wjgnet.com/1007-9327/full/v29/i48/6198.htm
Number Citing Articles
1
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
2
Ryosuke Kikuchi, Kazuaki Okamoto, Tsuyoshi Ozawa, Junichi Shibata, Soichiro Ishihara, Tomohiro Tada. Endoscopic Artificial Intelligence for Image Analysis in Gastrointestinal NeoplasmsDigestion 2024; : 1 doi: 10.1159/000540251
3
Karina Fatakhova, Faisal Inayat, Hassam Ali, Pratik Patel, Attiq Ur Rehman, Arslan Afzal, Muhammad Sarfraz, Shiza Sarfraz, Gul Nawaz, Ahtshamullah Chaudhry, Rubaid Dhillon, Arthur Dilibe, Benjamin Glazebnik, Lindsey Jones, Emily Glazer. Gender disparities and woman-specific trends in Barrett’s esophagus in the United States: An 11-year nationwide population-based studyWorld Journal of Methodology 2025; 15(1): 97512 doi: 10.5662/wjm.v15.i1.97512
4
Charalampos Theocharopoulos, Spyridon Davakis, Dimitrios C. Ziogas, Achilleas Theocharopoulos, Dimitra Foteinou, Adam Mylonakis, Ioannis Katsaros, Helen Gogas, Alexandros Charalabopoulos. Deep Learning for Image Analysis in the Diagnosis and Management of Esophageal CancerCancers 2024; 16(19): 3285 doi: 10.3390/cancers16193285