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Review
. 2023 Feb 10;13(4):662.
doi: 10.3390/diagnostics13040662.

Artificial Intelligence-The Rising Star in the Field of Gastroenterology and Hepatology

Madalina Stan-Ilie  1   2 , Vasile Sandru  2 , Gabriel Constantinescu  1   2 , Oana-Mihaela Plotogea  1   2 , Ecaterina Mihaela Rinja  2 , Iulia Florentina Tincu  1   3 , Alexandra Jichitu  2 , Adriana Elena Carasel  2 , Andreea Cristina Butuc  2 , Bogdan Popa  1   2
Affiliations
Review

Artificial Intelligence-The Rising Star in the Field of Gastroenterology and Hepatology

Madalina Stan-Ilie et al. Diagnostics (Basel). .

Abstract

Artificial intelligence (AI) is a term that covers a multitude of techniques that are used in a manner that tries to reproduce human intelligence. AI is helpful in various medical specialties that use imaging for diagnostic purposes, and gastroenterology is no exception. In this field, AI has several applications, such as detecting and classifying polyps, detecting the malignancy in polyps, diagnosing Helicobacter pylori infection, gastritis, inflammatory bowel disease, gastric cancer, esophageal neoplasia, and pancreatic and hepatic lesions. The aim of this mini-review is to analyze the currently available studies regarding AI in the field of gastroenterology and hepatology and to discuss its main applications as well as its main limitations.

Keywords: CT; artificial intelligence; endoscopic ultrasound; endoscopy; gastrointestinal diseases; radiology.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
NBI visualization of colon polyps.
See this image and copyright information in PMC

References

    1. Berbís M.A., Aneiros-Fernández J., Mendoza Olivares F.J., Nava E., Luna A. Role of Artificial Intelligence in Multidisciplinary Imaging Diagnosis of Gastrointestinal Diseases. World J. Gastroenterol. 2021;27:4395–4412. doi: 10.3748/wjg.v27.i27.4395. - DOI - PMC - PubMed
    1. Artificial Intelligence Committee House of Lords-AI in the UK: Ready, Willing and Able? [(accessed on 2 January 2021)]. Available online: https://Publications.Parliament.Uk/Pa/Ld201719/Ldselect/Ldai/100/10005.Html.
    1. Pannala R., Krishnan K., Melson J., Parsi M.A., Schulman A.R., Sullivan S., Trikudanathan G., Trindade A.J., Watson R.R., Maple J.T., et al. Artificial Intelligence in Gastrointestinal Endoscopy. VideoGIE. 2020;5:598–613. doi: 10.1016/j.vgie.2020.08.013. - DOI - PMC - PubMed
    1. Chartrand G., Cheng P.M., Vorontsov E. Deep Learning: A Primer for Radiologists. Radiographics. 2017;37:2113–2131. doi: 10.1148/rg.2017170077. - DOI - PubMed
    1. Byrne M.F., Chapados N., Soudan F., Oertel C., Linares Pérez M., Kelly R., Iqbal N., Chandelier F., Rex D.K. Real-Time Differentiation of Adenomatous and Hyperplastic Diminutive Colorectal Polyps during Analysis of Unaltered Videos of Standard Colonoscopy Using a Deep Learning Model. Gut. 2019;68:94–100. doi: 10.1136/gutjnl-2017-314547. - DOI - PMC - PubMed

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