To validate the accuracy of the Epidemiology-based Mortality Score in Status Epilepticus (EMSE) in predicting the risk of death at 30 days in a large cohort of patients with status epilepticus (SE) using a machine-learning system.

Machine-learning validation through decision-tree analysis of the Epidemiology-based Mortality Score in Status Epilepticus / Brigo, F., Turcato, G., Lattanzi, S., Orlandi, N., Turchi, G., Zaboli, A., Giovannini, G., Meletti, S.. - In: EPILEPSIA. - ISSN 0013-9580. - 63:10(2022), pp. 2507-2518. [10.1111/epi.17372]

Machine-learning validation through decision-tree analysis of the Epidemiology-based Mortality Score in Status Epilepticus

Meletti, Stefano
2022-01-01

Abstract

To validate the accuracy of the Epidemiology-based Mortality Score in Status Epilepticus (EMSE) in predicting the risk of death at 30 days in a large cohort of patients with status epilepticus (SE) using a machine-learning system.
2022
Machine-learning validation through decision-tree analysis of the Epidemiology-based Mortality Score in Status Epilepticus / Brigo, F., Turcato, G., Lattanzi, S., Orlandi, N., Turchi, G., Zaboli, A., Giovannini, G., Meletti, S.. - In: EPILEPSIA. - ISSN 0013-9580. - 63:10(2022), pp. 2507-2518. [10.1111/epi.17372]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/3058098
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