Using machine learning and big data for the prediction of venous thromboembolic events after spine surgery: A single-center retrospective analysis of multiple models on a cohort of 6869 patients

OBJECTIVE: Venous thromboembolic event (VTE) after spine surgery is a rare but potentially devastating complication. With the advent of machine learning, an opportunity exists for more accurate prediction of such events to aid in prevention and treatment. METHODS: Seven models were screened using 10...

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Detalles Bibliográficos
Autores principales: Hopkins, Benjamin S., Cloney, Michael B., Dhillon, Ekamjeet S., Texakalidis, Pavlos, Dallas, Jonathan, Nguyen, Vincent N., Ordon, Matthew, Tecle, Najib El, Chen, Thomas C., Hsieh, Patrick C., Liu, John C., Koski, Tyler R., Dahdaleh, Nader S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10583792/
https://www.ncbi.nlm.nih.gov/pubmed/37860027
http://dx.doi.org/10.4103/jcvjs.jcvjs_69_23

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10583792/
https://www.ncbi.nlm.nih.gov/pubmed/37860027
http://dx.doi.org/10.4103/jcvjs.jcvjs_69_23

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