Artificial intelligence in celiac disease. (October 2020)

• Record Type: Journal Article
• Authors: Sana, Muhammad Khawar; Hussain, Zeshan M.; Shah, Pir Ahmad; Maqsood, Muhammad Haisum
• Is Part Of: Computers in biology and medicine. Volume 125(2020)
• Publication Date: 2020-10
• Subjects: Artificial intelligence -- Machine learning -- Deep learning -- Celiac disease -- Systematic review; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2020.103996
• Languages: English
• ISSNs: 0010-4825

Abstract

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. Highlights: Artificial intelligence-based models show promise in healthcare. Celiac disease is frequently missed and challenging to diagnose. Deep learning can be effective in early detection and management of celiac disease.