Use of AI in accurate diagnosis of TB using Medical Imaging: a promising result from UAE
Introduction: Dubai Health Authority and Agfa HealthCare recognized the potential of Machine Learning Algorithms and AI enabled workflows in medical imaging three years ago. With a strategic goal for workflow automation and fast access to diagnostic imaging results, an approach to enable Augmented Intelligence in medical imaging was devised to consider application of AI in Chest X-Ray screening.
Aim: To compare sensitivity and specificity of AI technology in screening Tuberculosis across 20 Medical Fitness Centers in Dubai, in 2015 to validate AI enabled automated Chest X-Ray screening workflow.
Method: The DHA provided Agfa HealthCare anonymized Chest X-Rays samples, half of which were categorized as Normal X-Rays, and remaining half with Tuberculosis findings based on lab confirmation. Agfa HealthCare and VRVis Vienna analyzed these anonymized X-Rays between 2015-2016 and developed a workflow concept with Machine Learning Algorithm post image processing that include edge detection and image segmentation.
Conclusion: Based on the analysis of results so far, and how the AI Algorithm is performing, cases that are flagged for a disease like Tuberculosis would get followed up on the same day
Published By European Respiratory Society
Print ISSN 0903-1936
Online ISSN 1399-3003 History Published online November 19, 2018.
European Respiratory Journal 2018 52: Suppl. 62, OA5171.