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Machine learning integration of scleroderma histology and gene expression identifies fibroblast polarisation as a hallmark of clinical severity and improvement

Kimberly Showalter, Robert Spiera, Cynthia M. Magro, Phaedra Agius, Viktor Martyanov, Jennifer M. Franks, Roshan Sharma, Heather Geiger, Tammara Wood, Yaxia Zhang, Caryn Hale, Jackie Finik, Michael L. Whitfield, Dana E. Orange, Jessica Gordon

2020Annals of the Rheumatic Diseases30 citationsDOIOpen Access PDF

Topics & Concepts

MedicineGene expressionScleroderma (fungus)HistologyCD34PathologySystemic sclerodermaGene expression profilingFibroblastGeneStem cellBiologyIn vitroInoculationBiochemistryDermatomyositisGeneticsSystemic Sclerosis and Related DiseasesConnective Tissue Growth Factor ResearchLymphatic System and Diseases
Machine learning integration of scleroderma histology and gene expression identifies fibroblast polarisation as a hallmark of clinical severity and improvement | Litcius