Validation of a Machine Learning Approach for Venous Thromboembolism Risk Prediction in Oncology

Using kernel machine learning (ML) and random optimization (RO) techniques, we recently developed a set of venous thromboembolism (VTE) risk predictors, which could be useful to devise a web interface for VTE risk stratification in chemotherapy-treated cancer patients. This study was designed to val...

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Dades bibliogràfiques
Publicat a:Dis Markers
Autors principals: Ferroni, Patrizia, Zanzotto, Fabio M., Scarpato, Noemi, Riondino, Silvia, Guadagni, Fiorella, Roselli, Mario
Format: Artigo
Idioma:Inglês
Publicat: Hindawi 2017
Matèries:
Research Article
Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC5623790/
https://ncbi.nlm.nih.gov/pubmed/29104344
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2017/8781379
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