19:15[Articles] Machine learning for classification of hypertension subtypes using multi-omics: A multi-centre, retrospective, data-driven study -
Parminder S. Reel, Smarti Reel, Josie C. van Kralingen, Katharina Langton, Katharina Lang, Zoran Erlic, Casper K. Larsen, Laurence Amar, Christina Pamporaki, Paolo Mulatero, Anne Blanchard, Marek Kabat, Stacy Robertson, Scott M. MacKenzie, Angela E. Taylor, Mirko Peitzsch, Filippo Ceccato, Carla Scaroni, Martin Reincke, Matthias Kroiss, Michael C. Dennedy, Alessio Pecori, Silvia Monticone, Jaap Deinum, Gian Paolo Rossi, Livia Lenzini, John D. McClure, Thomas Nind, Alexandra Riddell, Anthony Stell, Christian Cole, Isabella Sudano, Cornelia Prehn, Jerzy Adamski, Anne-Paule Gimenez-Roqueplo, (...)
Lancet - Hypertension
We have developed a ML pipeline to distinguish different EHT subtypes from PHT using multi-omics data. This innovative approach to stratification is an advancement towards the development of a diagnostic tool for EHT patients, significantly increasing testing throughput and accelerating (...) (eBioMedicine 84, (2022))