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, A., Aretusi, G., Manganelli, F., Sekiguchi, Y., Magy, L., Tozza, S., Tsuneyama, A., Lefour, S., Kuwabara, S., Santoro, L., Ippoliti, L.. - 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.| File | Dimensione | Formato | |
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