Background and Aims
Abbreviations:BE (Barrett’s esophagus), EAC (esophageal adenocarcinoma), EET (endoscopic eradication therapy), NDBE (nondysplastic Barrett’s esophagus), HGD (high-grade dysplasia), LGD (low-grade dysplasia), WSI (whole-slide image), YOLO (you only look once)
Purchase one-time access:Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
One-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
- Cancer statistics, 2020.CA Cancer J Clin. 2020; 70: 7-30
- Incidence of esophageal adenocarcinoma in patients with Barrett's esophagus and high-grade dysplasia: a meta-analysis.Gastrointest Endosc. 2008; 67: 394-398
- ACG clinical guideline: diagnosis and management of Barrett's esophagus.Am J Gastroenterol. 2016; 111 (quiz 51): 30-50
- ASGE guideline on screening and surveillance of Barrett's esophagus.Gastrointest Endosc. 2019; 90: 335-359
- Diagnosis and grading of dysplasia in Barrett's oesophagus.J Clin Pathol. 2006; 59: 1029-1038
- Low-grade dysplasia in Barrett's esophagus: overdiagnosed and underestimated.Am J Gastroenterol. 2010; 105: 1523-1530
Huang G, Liu Z, Maaten LVD, et al. Densely connected convolutional networks. Presented at the 2017 IEEE Conference on Computer Vision and Pattern Recognition, July 21-26, 2017. Available at: https://ieeexplore.ieee.org/document/8099726. Accessed July 21, 2022.
- A novel training algorithm for convolutional neural network.Complex Intell Syst. 2016; 2: 221-234
- Automatic detection of erosions and ulcerations in wireless capsule endoscopy images based on a deep convolutional neural network.Gastrointest Endosc. 2019; 89: 357-363
- Utilisation of artificial intelligence for the development of an EUS-convolutional neural network model trained to enhance the diagnosis of autoimmune pancreatitis.Gut. 2021; 70: 1335-1344
- Attention-based deep neural networks for detection of cancerous and precancerous esophagus tissue on histopathological slides.JAMA Netw Open. 2019; 2e1914645
- Machine learning for grading and prognosis of esophageal dysplasia using mass spectrometry and histological imaging.Comput Biol Med. 2021; 138104918
- Neural network ensembles.IEEE Trans Pattern Anal Machine Intell. 1990; 12: 993-1001
- Current issues in Barrett's esophagus and Barrett's-related dysplasia.Mod Pathol. 2015; 28: S1-S6
- Barrett's esophagus: a comprehensive and contemporary review for pathologists.Am J Surg Pathol. 2016; 40: e45-e66
- Scikit-learn: machine learning in Python.J Machine Learn Res. 2011; 12: 2825-2830
- Ensemble deep learning: a review.ArXiv. 2021; (abs/2104.02395)
Girshick R, Donahue J, Darrell T, et al. Rich feature hierarchies for accurate object detection and semantic segmentation. Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition: IEEE Computer Society; 2014. p. 580-7.
- You only look once: unified, real-time object detection.ArXiv. 2015; 150602640
- Going deeper with convolutions.ArXiv. 2014; : 1409-4842
- ImageNet classification with deep convolutional neural networks.in: Proceedings of the 25th International Conference on Neural Information Processing Systems. 1. Curran Associates Inc, Lake Tahoe, NV2012: 1097-1105
- Gradient-based learning applied to document recognition.Proc IEEE. 1998; 86: 2278-2324
- Reproducibility of the diagnosis of dysplasia in Barrett esophagus: a reaffirmation.Hum Pathol. 2001; 32: 368-378
- Discordance among pathologists in the United States and Europe in diagnosis of low-grade dysplasia for patients with Barrett's esophagus.Gastroenterology. 2017; 152: 564-570
- Variable pathologic interpretation of columnar lined esophagus by general pathologists in community practice.Gastrointest Endosc. 1999; 50: 23-26
- Predictors of progression in Barrett's esophagus with low-grade dysplasia: results from a multicenter prospective BE registry.Am J Gastroenterol. 2017; 112: 867-873
- Patients with Barrett’s esophagus and confirmed persistent low-grade dysplasia are at increased risk for progression to neoplasia.Gastroenterology. 2017; 152: 993-1001
- Incidence of esophageal adenocarcinoma in Barrett's esophagus with low-grade dysplasia: a systematic review and meta-analysis.Gastrointest Endosc. 2014; 79: 897-909.e4
- Development and pilot testing of decision aid for shared decision making in Barrett's esophagus with low-grade dysplasia.J Clin Gastroenterol. 2021; 55: 36-42
- OpenMMLab detection toolbox and benchmark.(Available at:)Accessed December 21, 2021)
- Open mmlab detection toolbox and benchmark.(Available at:)Accessed July 21, 2022)
- GLO-YOLO: a dynamic glomerular detecting and slicing model in whole slide images.in: Proceedings of the 2020 Conference on Artificial Intelligence and Healthcare. Association for Computing Machinery, Taiyuan, China2020: 229-233
- Learning to detect lymphocytes in immunohistochemistry with deep learning.Med Image Anal. 2019; 58101547
- Microsoft COCO: common objects in context.in: Computer Vision—ECCV 2014. Springer International Publishing, Cham, Switzerland2014
- Deep residual learning for image recognition.ArXiv. 2015; 151203385
Deng J, Dong W, Socher R, et al. ImageNet: a large-scale hierarchical image database. Available at: https://ieeexplore.ieee.org/document/5206848. Accessed July 21, 2022.
- Fastai. A layered API for deep learning.Information. 2020; 11
- Densely connected convolutional networks.ArXiv. 2016; 160806993
DISCLOSURE: The following authors disclosed financial relationships: B. J. Erickson: Officer at FlowSIGMA, Inc and Yunu, Inc. P. G. Iyer: Research funding from Exact Sciences, Pentax Medical, and Cernostics; consultant for Exact Sciences, Medtronic, Ambu Medical, Symple Surgical, and Cernostics. C. L. Leggett: research support for Verily Life. All other authors disclosed no financial relationships. Research support for this study was provided by Mayo Clinic Division of Gastroenterology and Hepatology Innovation Award and the Freeman Foundation.
DIVERSITY, EQUITY, AND INCLUSION: One or more of the authors of this paper self-identifies as an under-represented gender minority in science. While citing references scientifically relevant for this work, we actively worked to promote gender balance in our reference list.