Abstract
The 2016 Cochrane Review identified Magnetic Resonance Imaging (MRI) and Transvaginal Ultrasound scans (TVUS) as the most diagnostic non-invasive test for endometriosis. This led to IMAGENDO, which uses Artificial Intelligence (AI) to model digital data from these two imaging modalities to improve the accuracy of endometriosis non-invasive diagnostics. The IMAGENDO team have developed a novel, award winning, multimodal approach to improve the sensitivity and specificity of endometriosis imaging. The talk will describe some of the methods used, the impact AI has had on diagnostic accuracy and the challenges faced and yet to be overcome. The likely role of AI in future endometriosis diagnostics will be speculated upon.
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