Barrett esophagus: What to expect from Artificial Intelligence?
- The evaluation and assessment of Barrett’s esophagus is challenging for both expert and nonexpert endoscopists. However, the early diagnosis of cancer in Barrett’s esophagus is crucial for its prognosis, and could save costs. Pre-clinical and clinical studies on the application of Artificial Intelligence (AI) in Barrett’s esophagus have shown promising results. In this review, we focus on theThe evaluation and assessment of Barrett’s esophagus is challenging for both expert and nonexpert endoscopists. However, the early diagnosis of cancer in Barrett’s esophagus is crucial for its prognosis, and could save costs. Pre-clinical and clinical studies on the application of Artificial Intelligence (AI) in Barrett’s esophagus have shown promising results. In this review, we focus on the current challenges and future perspectives of implementing AI systems in the management of patients with Barrett’s esophagus.…
| Author: | Alanna EbigboORCiDGND, Christoph PalmOTHORCiDGND, Helmut Messmann |
|---|---|
| DOI: | https://doi.org/10.1016/j.bpg.2021.101726 |
| ISSN: | 1521-6918 |
| Parent Title (English): | Best Practice & Research Clinical Gastroenterology |
| Publisher: | Elsevier |
| Document Type: | Article |
| Language: | English |
| Year of first Publication: | 2021 |
| Release Date: | 2021/03/10 |
| Tag: | Adenocarcinoma; Artificial intelligence; Barrett; Convolutional neural networks; Deep learning |
| GND Keyword: | Deep Learning; Künstliche Intelligenz; Computerunterstützte Medizin |
| Volume: | 52-53 |
| Issue: | June-August |
| Article Number: | 101726 |
| Institutes: | Fakultät Informatik und Mathematik |
| Research Center of Biomedical Engineering - RCBE | |
| Research Center of Health Sciences and Technology - RCHST | |
| Research Center for Artificial Intelligence - RCAI | |
| Fakultät Informatik und Mathematik / Labor Regensburg Medical Image Computing (ReMIC) | |
| Begutachtungsstatus: | peer-reviewed |
| research focus: | Gesundheit und Soziales |
| Licence (German): | |
| Frontdoor-URL: | https://opus4.kobv.de/opus4-oth-regensburg/1461 |
