Skip to primary content


Full title: The LiverTRAIL software for early detection of severe liver fibrosis in patients with alcoholic and non-alcoholic fatty liver disease

Project period

Start: December 2018
End: November 2022


This PhD project aimed to 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 – was algorithm-based, combining results from routine liver blood tests into multiple diagnostic algorithms, thus utilising computational power for large-scale data aggregation and pattern recognition.

The aim was that LiverTRAIL could transform knowledge from original research data into a rational decision tool for the general practitioner. 

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

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

The project hypothesised that through the implementation of LiverTRAIL in the primary sector, it would possible to achieve early detection of patients with asymptomatic, early-stage severe fibrosis and cirrhosis.



The project was funded by Innovation Fund Denmark.

Read more about the first results from the project in the article Artificial intelligence outperforms standard blood-based scores in identifying liver fibrosis patients in primary care. The article was published in Scientific Reports, part of the Nature Portfolio.

Katrine Prier Lindvig

Katrine Prier Lindvig

PhD student, MD

FLASH – Center for Liver Research

(+45) 28 83 87 54