Artificial intelligence automates and augments baseline impedance measurements from pH-impedance studies in gastroesophageal reflux disease
Author:
Funder
Thomas and Mary Eckert Fellowship Clinical Research Fund
Publisher
Springer Science and Business Media LLC
Subject
Gastroenterology
Link
http://link.springer.com/content/pdf/10.1007/s00535-020-01743-2.pdf
Reference17 articles.
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2. Frazzoni M, Savarino E, de Bortoli N, et al. Analyses of the post-reflux swallow-induced peristaltic wave index and nocturnal baseline impedance parameters increase the diagnostic yield of impedance-pH monitoring of patients with reflux disease. Clin Gastroenterol Hepatol. 2016;14:40–6.
3. Patel A, Wang D, Sainani N, et al. Distal mean nocturnal baseline impedance on pH-impedance monitoring predicts reflux burden and symptomatic outcome in gastro-oesophageal reflux disease. Aliment Pharmacol Ther. 2016;44:890–8.
4. Rengarajan A, Savarino E, Della Coletta M, et al. Mean nocturnal baseline impedance correlates with symptom outcome when acid exposure time is inconclusive on esophageal reflux monitoring. Clin Gastroenterol Hepatol. 2020;18:589–95.
5. Jin EH, Lee D, Bae JH, et al. Improved accuracy in optical diagnosis of colorectal polyps using convolutional neural networks with visual explanations. Gastroenterology. 2020;158:2169–79.
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