LiverTrail

Aim

This PhD project will develop and validate a decision aid for use in primary health care to assess the risk of advanced fibrosis in patients with alcoholic- and non-alcoholic fatty liver disease. The decision aid – LiverTRAIL – works algorithm-based, by combining results from routine liver blood tests into multiple diagnostic algorithms, thus utilising computational power for large-scale data aggregation and pattern recognition.

Our aim is that LiverTRAIL can transform knowledge from original research data into a rational decision tool for the general practitioner. 

LiverTRAIL will unite three main challenges within the study of fatty liver disease:

1. Identify patients with severe fibrosis due to ALD and NAFLD (rule-in).
2. Exclude patients with ALD and NAFLD at very low risk of advanced fibrosis from further diagnostic investigations (rule-out).
3. Monitor patients at high- and moderate risk of advanced fibrosis for disease progression and fibrosis improvement, e.g. during anti-fibrotic treatment.

We hypothesize that through the implementation of LiverTRAIL in the primary sector, it is possible to achieve early detection of patients with asymptomatic, early-stage severe fibrosis and cirrhosis.

Participants

• FLASH – Centre for Liver Research, OUH
• Professor Esmaeil S. Nadimi, Applied AI and Data Science, The Maersk Mc-Kinney Moller Institute, Faculty of Engineering, SDU

Funding

The project is funded by Innovation Fund Denmark.