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Author Adadi, Amina ♦ Adadi, Safae ♦ Berrada, Mohammed
Editor Fdez-Riverola, Florentino
Source Hindawi
Content type Text
Publisher Hindawi
File Format PDF
Copyright Year ©2019
Language English
Abstract Machine learning has undergone a transition phase from being a pure statistical tool to being one of the main drivers of modern medicine. In gastroenterology, this technology is motivating a growing number of studies that rely on these innovative methods to deal with critical issues related to this practice. Hence, in the light of the burgeoning research on the use of machine learning in gastroenterology, a systematic review of the literature is timely. In this work, we present the results gleaned through a systematic review of prominent gastroenterology literature using machine learning techniques. Based on the analysis of 88 journal articles, we delimit the scope of application, we discuss current limitations including bias, lack of transparency, accountability, and data availability, and we put forward future avenues.
ISSN 16878027
Learning Resource Type Article
Publisher Date 2019-04-02
Rights License This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
e-ISSN 16878035
Journal Advances in Bioinformatics
Volume Number 2019
Page Count 24


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