The final sponsored challenge is here courtesy of the Pistoia Alliance member; Promeditec.
These challenges are designed to show how deep learning can work with life science and health related data to make an impact on advancing research into tackling disease and supporting patients.
The Challenge: Accelerate early diagnosis of Thoracic Aortic Aneurysm (TAA) through machine learning
Promeditec, as part of the under-development project InSilicoTrials.com, would like you to demonstrate the ability of deep learning to help accelerate early diagnosis and improve surgical treatment of Thoracic Aortic Aneurysm (TAA).
TAA is a “ballooning” of the upper aspect of the aorta, present primarily in the thorax above the diaphragm. The mortality rate as a consequence of untreated or unrecognized TAA, due to aortic dissection or rupture, was 2.78 per 100.000 in 2010, increasing from 2.49 per 100.000 in 1990.
Automatic reconstruction of the aortic walls, from patient’s medical images, combined with computational fluid dynamics simulations, based on patient-specific hemodynamics, can provide very important information (otherwise undetectable) on the evolution of TAA, to give surgeons precious indications during the surgical planning in order to reach the optimal patient-specific treatment.
We look forward to seeing you at the event.
For any questions on how to get involved as competitors, judges or provide a challenge, please contact David Proudlock.