AI and SWE in liver disease

Aim

In this project, we have developed a machine-learning algorithm with the ability to improve the diagnostic accuracy of SWE pictures in patients with chronic fatty liver disease. Specifically a convolutional neural network. In our second project, we take a step further and seek to improve the prognostic power of SWE pictures in chronic fatty liver disease patients. The aim is to add a layer of prognostication to SWE pictures – by giving the clinician a tool to foresee liver-related events.

Participants

• FLASH – Center for Liver Research, OUH
• Professor Thiusius Rajeeth Savarimuthu, SDU Robotics, The Maersk Mc-Kinney Moller Institute, Faculty of Engineering, SDU

Funding

The project is funded by FLASH – Center for Liver Research, OUH.