The interpretation of electrophysiological findings may lead to misdiagnosis in polyneuropathies. We investigated the electrodiagnostic accuracy of three supervised learning algorithms (SLAs): shrinkage discriminant analysis, multinomial logistic regression, and support vector machine (SVM), and three expert and three trainee neurophysiologists.

Electrodiagnostic accuracy in polyneuropathies: supervised learning algorithms as a tool for practitioners / Uncini, Antonino; Aretusi, Graziano; Manganelli, Fiore; Sekiguchi, Yukari; Magy, Laurent; Tozza, Stefano; Tsuneyama, Atsuko; Lefour, Sophie; Kuwabara, Satoshi; Santoro, Lucio; Ippoliti, Luigi. - In: NEUROLOGICAL SCIENCES. - ISSN 1590-1874. - (2020). [10.1007/s10072-020-04499-y]

Electrodiagnostic accuracy in polyneuropathies: supervised learning algorithms as a tool for practitioners

Manganelli, Fiore;Tozza, Stefano;Santoro, Lucio;
2020

Abstract

The interpretation of electrophysiological findings may lead to misdiagnosis in polyneuropathies. We investigated the electrodiagnostic accuracy of three supervised learning algorithms (SLAs): shrinkage discriminant analysis, multinomial logistic regression, and support vector machine (SVM), and three expert and three trainee neurophysiologists.
2020
Electrodiagnostic accuracy in polyneuropathies: supervised learning algorithms as a tool for practitioners / Uncini, Antonino; Aretusi, Graziano; Manganelli, Fiore; Sekiguchi, Yukari; Magy, Laurent; Tozza, Stefano; Tsuneyama, Atsuko; Lefour, Sophie; Kuwabara, Satoshi; Santoro, Lucio; Ippoliti, Luigi. - In: NEUROLOGICAL SCIENCES. - ISSN 1590-1874. - (2020). [10.1007/s10072-020-04499-y]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/808645
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