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Current Treatment Options in Gastroenterology

Erschienen in:

21.01.2020 | Colon (J Anderson, Section Editor)

Artificial Intelligence and Polyp Detection

verfasst von: Nicholas Hoerter, Seth A. Gross, Peter S. Liang

Erschienen in: Current Treatment Options in Gastroenterology | Ausgabe 1/2020

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Abstract

Purpose of review

This review highlights the history, recent advances, and ongoing challenges of artificial intelligence (AI) technology in colonic polyp detection.

Recent findings

Hand-crafted AI algorithms have recently given way to convolutional neural networks with the ability to detect polyps in real-time. The first randomized controlled trial comparing an AI system to standard colonoscopy found a 9% increase in adenoma detection rate, but the improvement was restricted to polyps smaller than 10 mm and the results need validation. As this field rapidly evolves, important issues to consider include standardization of outcomes, dataset availability, real-world applications, and regulatory approval.

Summary

AI has shown great potential for improving colonic polyp detection while requiring minimal training for endoscopists. The question of when AI will enter endoscopic practice depends on whether the technology can be integrated into existing hardware and an assessment of its added value for patient care.

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Titel: Artificial Intelligence and Polyp Detection
verfasst von: Nicholas Hoerter
Seth A. Gross
Peter S. Liang
Publikationsdatum: 21.01.2020
Verlag: Springer US
Erschienen in: Current Treatment Options in Gastroenterology / Ausgabe 1/2020
Print ISSN: 1092-8472
Elektronische ISSN: 1534-309X
DOI: https://doi.org/10.1007/s11938-020-00274-2

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Abstract

Purpose of review

Recent findings

Summary

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