Human-machine collaboration: bringing artificial intelligence into colonoscopy

Omer F Ahmad¹, Danail Stoyanov¹, Laurence B Lovat^{1

2}

Affiliations

¹ Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, London, UK.
² Division of Surgery and Interventional Science, University College London, London, UK.

Editorial

Omer F Ahmad et al. Frontline Gastroenterol. 2019 Apr.

. 2019 Apr;10(2):198-199.

doi: 10.1136/flgastro-2018-101047. Epub 2018 Oct 15.

Omer F Ahmad¹, Danail Stoyanov¹, Laurence B Lovat^{1

2}

¹ Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, London, UK.
² Division of Surgery and Interventional Science, University College London, London, UK.

No abstract available

Keywords: colonic adenomas; colonic polyps; colonoscopy; colorectal cancer; computerised image analysis.

Conflict of interest statement

Competing interests: None declared.

1. van Rijn JC, Reitsma JB, Stoker J, et al. . Polyp miss rate determined by tandem colonoscopy: a systematic review. Am J Gastroenterol 2006;101:343–50. 10.1111/j.1572-0241.2006.00390.x - DOI - PubMed
1. Kaminski MF, Regula J, Kraszewska E, et al. . Quality indicators for colonoscopy and the risk of interval cancer. N Engl J Med 2010;362:1795–803. 10.1056/NEJMoa0907667 - DOI - PubMed
1. Byrne MF, Shahidi N, Rex DK. Will computer-aided detection and diagnosis revolutionize colonoscopy? Gastroenterology 2017;153:1460–4. 10.1053/j.gastro.2017.10.026 - DOI - PubMed
1. Chartrand G, Cheng PM, Vorontsov E, et al. . Deep learning: a primer for radiologists. Radiographics 2017;37:2113–31. 10.1148/rg.2017170077 - DOI - PubMed
1. Esteva A, Kuprel B, Novoa RA, et al. . Dermatologist-level classification of skin cancer with deep neural networks. Nature 2017;542:115–8. 10.1038/nature21056 - DOI - PMC - PubMed