0000000000625621
AUTHOR
Gianluca Perseghin
Setting up of a machine learning algorithm for the identification of severe liver fibrosis profile in the general US population cohort
Background: The progress of digital transformation in clinical practice opens the door to transforming the current clinical line for liver disease diagnosis from a late-stage diagnosis approach to an early-stage based one. Early diagnosis of liver fibrosis can prevent the progression of the disease and decrease liver-related morbidity and mortality. We developed here a machine learning (ML) algorithm containing standard parameters that can identify liver fibrosis in the general US population.Materials and methods: Starting from a public database (National Health and Nutrition Examination Survey, NHANES), representative of the American population with 7265 eligible subjects (control populati…
Glycated Albumin for Glycemic Control in T2DM Population: A Multi-Dimensional Evaluation.
Lucrezia Ferrario,1 Fabrizio Schettini,1 Angelo Avogaro,2 Chiara Bellia,3 Federico Bertuzzi,4 Graziella Bonetti,5 Antonio Ceriello,6 Marcello Ciaccio,3,7 Massimiliano Corsi Romanelli,8,9 Elena Dozio,9 Luca Falqui,10 Angela Girelli,11 Antonio Nicolucci,12 Gianluca Perseghin,13,14 Mario Plebani,15 Umberto Valentini,11 Martina Zaninotto,15 Silvana Castaldi,9,16 Emanuela Foglia1 1Centre for Health Economics, Social and Health Care Management, Università Carlo Cattaneo - LIUC, Castellanza, Italy; 2Department of Medicine, University-Hospital of Padova, Padova, Italy; 3Section of Clinical Biochemistry and Clinical Molecular Medicine, Department of Biopathology and Medical Biotechnologie…