Cardiovascular Risk Prediction in Ankylosing Spondylitis: From Traditional Scores to Machine Learning Assessment

INTRODUCTION: The performance of seven cardiovascular (CV) risk algorithms is evaluated in a multicentric cohort of ankylosing spondylitis (AS) patients. Performance and calibration of traditional CV predictors have been compared with the novel paradigm of machine learning (ML). METHODS: A retrospec...

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Detalles Bibliográficos
Autores principales: Navarini, Luca, Caso, Francesco, Costa, Luisa, Currado, Damiano, Stola, Liliana, Perrotta, Fabio, Delfino, Lorenzo, Sperti, Michela, Deriu, Marco A., Ruscitti, Piero, Pavlych, Viktoriya, Corrado, Addolorata, Di Benedetto, Giacomo, Tasso, Marco, Ciccozzi, Massimo, Laudisio, Alice, Lunardi, Claudio, Cantatore, Francesco Paolo, Lubrano, Ennio, Giacomelli, Roberto, Scarpa, Raffaele, Afeltra, Antonella
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Healthcare 2020
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7695785/
https://www.ncbi.nlm.nih.gov/pubmed/32939675
http://dx.doi.org/10.1007/s40744-020-00233-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7695785/
https://www.ncbi.nlm.nih.gov/pubmed/32939675
http://dx.doi.org/10.1007/s40744-020-00233-4

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