A machine-learning model for reducing misdiagnosis in heparin-induced thrombocytopenia: A prospective, multicenter, observational studyResearch in context

A machine-learning model for reducing misdiagnosis in heparin-induced thrombocytopenia: A prospective, multicenter, observational studyResearch in context

Summary: Background: Diagnosing heparin-induced thrombocytopenia (HIT) at the bedside remains challenging, exposing a significant number of patients at risk of delayed diagnosis or overtreatment. We hypothesized that machine-learning algorithms could be utilized to develop a more accurate and user-...

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Bibliographic Details
Main Authors: Henning Nilius, Adam Cuker, Sigve Haug, Christos Nakas, Jan-Dirk Studt, Dimitrios A. Tsakiris, Andreas Greinacher, Adriana Mendez, Adrian Schmidt, Walter A. Wuillemin, Bernhard Gerber, Johanna A. Kremer Hovinga, Prakash Vishnu, Lukas Graf, Alexander Kashev, Raphael Sznitman, Tamam Bakchoul, Michael Nagler
Format: Article
Language:English
Published: Elsevier 2023-01-01
Series:EClinicalMedicine
Subjects:
Heparin
Low-molecular-weight
Thrombocytopenia
Anticoagulants
Platelet count
Heparin-induced thrombocytopenia
Online Access:http://www.sciencedirect.com/science/article/pii/S2589537022004746

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http://www.sciencedirect.com/science/article/pii/S2589537022004746

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