Toward interpretability of machine learning methods for the classification of patients with major depressive disorder based on functional network measures.

Andreev, Andrey V; Kurkin, Semen A; Stoyanov, Drozdstoy; Badarin, Artem A; Paunova, Rossitsa; Hramov, Alexander E

Andreev, Andrey V; Kurkin, Semen A; Stoyanov, Drozdstoy; Badarin, Artem A; Paunova, Rossitsa; Hramov, Alexander E.

Afiliación

Andreev AV; Baltic Center for Neurotechnology and Artificial Intelligence, Immanuel Kant Baltic Federal University, 14, A. Nevskogo str., Kaliningrad 236016, Russia.
Kurkin SA; Baltic Center for Neurotechnology and Artificial Intelligence, Immanuel Kant Baltic Federal University, 14, A. Nevskogo str., Kaliningrad 236016, Russia.
Stoyanov D; Department of Psychiatry and Medical Psychology, Research Institute, Medical University Plovdiv, 15A Vassil Aprilov Blvd., Plovdiv 4002, Bulgaria.
Badarin AA; Baltic Center for Neurotechnology and Artificial Intelligence, Immanuel Kant Baltic Federal University, 14, A. Nevskogo str., Kaliningrad 236016, Russia.
Paunova R; Department of Psychiatry and Medical Psychology, Research Institute, Medical University Plovdiv, 15A Vassil Aprilov Blvd., Plovdiv 4002, Bulgaria.
Hramov AE; Baltic Center for Neurotechnology and Artificial Intelligence, Immanuel Kant Baltic Federal University, 14, A. Nevskogo str., Kaliningrad 236016, Russia.

Chaos ; 33(6)2023 Jun 01.

Article en En | MEDLINE | ID: mdl-37318340

Asunto(s)

Trastorno Depresivo Mayor; Humanos; Mapeo Encefálico/métodos; Máquina de Vectores de Soporte; Aprendizaje Automático; Algoritmos

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Trastorno Depresivo Mayor Límite: Humans Idioma: En Revista: Chaos Asunto de la revista: CIENCIA Año: 2023 Tipo del documento: Article País de afiliación: Rusia Pais de publicación: Estados Unidos

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