Machine learning classifier:Diagnosing Kidney Transplant Diseases


Jesper Kers is renal and transplant pathologist at the Amsterdam UMC and visiting research associate at the Van ’t Hoff Institute for Molecular Sciences (HIMS) and the Ragon Institute of MGH, MIT & Harvard

Garry Corthals is Chair and professor of Biomolecular Systems Analytics at the University of Amsterdam, visiting professor at M4I of Maastricht University and guest professor at the Amsterdam UMC.

Alexander Schönhuth is professor of Genome Data Science at the Institute of Biodynamics and Biocomplexity, Utrecht University. He leads the Genome Data Science research team at the Informatics Institute (CWI) in Amsterdam.

Project description

Kidney transplantation is the preferred treatment for end-stage kidney disease, but after transplantation, various diseases can threaten the health of the donor kidney. The most prominent causes of transplant failure are immunological rejection, viral infections and medication toxicity. Due to the considerable difficulty in diagnosing these transplant diseases based on microscopic analysis by a pathologist, novel methods that can detect these disease processes on a molecular level are necessary. The group developed a pipeline for comprehensive and reproducible analysis of hundreds to thousands of proteins from kidney tissue by SWATH mass spectrometry. With this seed grant, this multidisciplinary team with expertise on pathology, proteomics and AI will determine whether a novel ensemble machine learning feature selection strategy can be used to determine robust proteomics-based patterns that are able to differentiate between different disease states with the final goal to translate these findings into practice and aid with clinical decision making.