Team 12: ML algorithm for staging of liver disease

Fatty liver disease progresses though several stages and the diagnosis of the stage is instrumental treatment and prognosis. The current gold standard diagnosis is a core liver punch biopsy which can lead complications and suffers from sample bias due to a low volume of tissue taken. The McDonald Lab has devolved a lipidomics platform using mass spectroscopy along with shotgun lipidomics to measure thousands of known and unknown lipids easily collected via a plasma sample taken from a patient. The focus of this project is to develop a machine learning algorithm using the plasma lipid data provided to provide staging for a patient’s liver disease diagnosis. The data consists of about 20 deidentified samples for each of the diagnosis stages with the ground truth known from the core liver punch biopsy.

Team Lead: Jeffrey McDonald, Molecular Genetics, www.utsouthwestern.edu//education/medical-school/departments/molecular-genetics

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