Article

Machine learning enables new insights into clinical significance of and genetic contributions to liver fat accumulation

2020-09-03

Abstract excerpt

Excess accumulation of liver fat – termed hepatic steatosis when fat accounts for > 5.5% of liver content – is a leading risk factor for end-stage liver disease and is strongly associated with important cardiometabolic disorders. Using a truth dataset of 4,511 UK Biobank participants with liver fat previously quantified via abdominal MRI imaging, we developed a machine learning algorithm to quantify liver fat with...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: d4518069-6720-5862-aeb6-d851b7e4573e
DOI: 10.1101/2020.09.03.20187195

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Machine learning enables new insights into clinical significance of and genetic contributions to liver fat accumulationDOI 10.1101/2020.09.03.20187195Read

Machine learning enables new insights into genetic contributions to liver fat accumulationSemantic proximity Read

Machine learning across multiple imaging and biomarker modalities in the UK Biobank improves genetic discovery for liver fat accumulationSemantic proximity Read

Unravelling genetic susceptibility and causal factors in liver health using MRI quantification of inflammation, fat and iron in the liver.Semantic proximity Read

Genome-wide association study of liver fat, iron, and extracellular fluid fraction in the UK BiobankSemantic proximity Read

Linking abdominal imaging traits to electronic health record phenotypesSemantic proximity Read

Clinical correlates of CT imaging-derived phenotypes among lean and overweight patients with hepatic steatosis.Semantic proximity Read

The link between liver fat and cardiometabolic diseases is highlighted by genome-wide association study of MRI-derived measures of body compositionSemantic proximity Read

Trans-ancestral rare variant association study with machine learning-based phenotyping for metabolic dysfunction-associated steatotic liver disease.Semantic proximity Read

Genome-wide Studies Reveal Genetic Risk Factors for Hepatic Fat Content.Semantic proximity Read

Exome-wide association analysis of CT imaging-derived hepatic fat in a medical biobank.Semantic proximity Read

The role of liver fat in cardiometabolic diseases is highlighted by genome-wide association study of MRI-derived measures of body compositionSemantic proximity Read

Deep Learning Reveals Liver MRI Features Associated With PNPLA3 I148M in Steatotic Liver Disease.Semantic proximity Read