Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2020 Oct:125:103996.
doi: 10.1016/j.compbiomed.2020.103996. Epub 2020 Sep 17.

Artificial intelligence in celiac disease

Affiliations
Review

Artificial intelligence in celiac disease

Muhammad Khawar Sana et al. Comput Biol Med. 2020 Oct.

Abstract

Celiac disease (CD) has been on the rise in the world and a large part of it remains undiagnosed. Novel methods are required to address the gaps in prompt detection and management. Artificial intelligence (AI) has seen an exponential surge in the last decade worldwide. With the advent of big data and powerful computational ability, we now have self-driving cars and smart devices in our daily lives. Huge databases in the form of electronic medical records and images have rendered healthcare a lucrative sector where AI can prove revolutionary. It is being used extensively to overcome the barriers in clinical workflows. From the perspective of a disease, it can be deployed in multiple steps i.e. screening tools, diagnosis, developing novel therapeutic agents, proposing management plans, and defining prognostic indicators, etc. We review the areas where it may augment physicians in the delivery of better healthcare by summarizing current literature on the use of AI in healthcare using CD as a model. We further outline major barriers to its large-scale implementations and prospects from the healthcare point of view.

Keywords: Artificial intelligence; Celiac disease; Deep learning; Machine learning; Systematic review.

PubMed Disclaimer

LinkOut - more resources