[artículo] 
inThe British Journal of Psychiatry > Año 2022 - Vol. 221 - No. 6 (Diciembre) . - pp. 732 - 739

Título :	Consistent brain structural abnormalities and multisite individualised classification of schizophrenia using deep neural networks
Tipo de documento:	texto impreso
Autores:	Yue Cui, Autor ; Chao Li, Autor ; Bing Liu, Autor
Fecha de publicación:	2023
Artículo en la página:	pp. 732 - 739
Idioma :	Inglés (eng) Idioma original : Inglés (eng)
Palabras clave:	Aprendizaje profundo, Materia gris, Metanálisis, Estudio multisitio, Esquizofrenia
Resumen:	Previous analyses of grey and white matter volumes have reported that schizophrenia is associated with structural changes. Deep learning is a data-driven approach that can capture highly compact hierarchical non-linear relationships among high-dimensional features, and therefore can facilitate the development of clinical tools for making a more accurate and earlier diagnosis of schizophrenia.
Link:	./index.php?lvl=notice_display&id=29953

[artículo] Consistent brain structural abnormalities and multisite individualised classification of schizophrenia using deep neural networks [texto impreso] / Yue Cui, Autor ; Chao Li, Autor ; Bing Liu, Autor . - 2023 . - pp. 732 - 739.
Idioma : Inglés (eng) Idioma original : Inglés (eng)
in The British Journal of Psychiatry > Año 2022 - Vol. 221 - No. 6 (Diciembre) . - pp. 732 - 739

Palabras clave:	Aprendizaje profundo, Materia gris, Metanálisis, Estudio multisitio, Esquizofrenia
Resumen:	Previous analyses of grey and white matter volumes have reported that schizophrenia is associated with structural changes. Deep learning is a data-driven approach that can capture highly compact hierarchical non-linear relationships among high-dimensional features, and therefore can facilitate the development of clinical tools for making a more accurate and earlier diagnosis of schizophrenia.
Link:	./index.php?lvl=notice_display&id=29953