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All Outputs (4)

Can machine-learning improve cardiovascular risk prediction using routine clinical data (2017)
Journal Article
Weng, S. F., Reps, J. M., Kai, J., Garibaldi, J. M., & Quereshi, N. (2017). Can machine-learning improve cardiovascular risk prediction using routine clinical data. PLoS ONE, 12(4), Article e0174944. https://doi.org/10.1371/journal.pone.0174944

Background Current approaches to predict cardiovascular risk fail to identify many people who would benefit from preventive treatment, while others receive unnecessary intervention. Machine-learning offers opportunity to improve accuracy by exploiti... Read More about Can machine-learning improve cardiovascular risk prediction using routine clinical data.

Venous thromboembolism in adults screened for Sickle Cell Trait: a population based cohort study with nested case-control analysis (2017)
Journal Article
Little, I., Vinogradova, Y., Orton, E., Kai, J., & Qureshi, N. (2017). Venous thromboembolism in adults screened for Sickle Cell Trait: a population based cohort study with nested case-control analysis. BMJ Open, 7(3), Article e012665. https://doi.org/10.1136/bmjopen-2016-012665

Objective: To determine whether sickle cell carriers (‘sickle cell trait’) have an increased risk of venous thromboembolism (VTE). Design: Cohort study with nested case-control analysis. Setting: General population with data from 609 UK gener... Read More about Venous thromboembolism in adults screened for Sickle Cell Trait: a population based cohort study with nested case-control analysis.