“We’re now in an era that some consider an AI renaissance, with enormous amounts of computing power — unimaginable only a few decades ago — now available to institutions and even individual researchers. Machine learning algorithms and AI are performing feats once considered to be exclusive domains for humans.” –Sushovan Guha, MD, PhD

In recent years, the prevalence of artificial intelligence (AI), machine learning (ML), and other breakthrough computer technologies has seen significant growth in medicine. Utilized by radiologists, neurologists, pathologists, and many other specialists, artificial intelligence has greatly expanded human capabilities and proved incredibly useful in parsing and aggregating enormous amounts of medical data. The ability to use this data to learn by itself and improve on its capabilities via machine learning has made AI a constantly self-evolving resource. Deep learning (DL) – a subset of ML – has shown exceptional performance in image analysis through its use of the convolutional neural network (CNN), adding to the growing list of AI applications in healthcare and gastroenterology specifically.

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