Performance of an Artificial Intelligence Model for Recognition and Quantitation of Histologic Features of Eosinophilic Esophagitis on Biopsy Samples

The Devastating Impact of Artificial Intelligence (AI) on the Traditional Ways of Practising Imaging and Cardiology Are ‘imagers’ an endangered species, and should trainees rethink their careers?

“…Of interest to the authors is the self-proclaimed superiority of AI in describing its level of performance as that which may 'rival or exceed human capabilities'. When it comes to image interpretation and pattern recognition, the superiority of AI may well be true given its rapid access to historical imaging data (the 'training' datasets) and the ability to analyse images in details relying on individual raw or pixel data, which has been tested in histological, [7] electrocardiographic [8] and indeed radiographic images. [9,10] All of these studies have concluded that AI simulates and supports human intuition and decision making as it relates to health care.…”