An Explainable Multimodal Neural Network Architecture for Predicting Epilepsy Comorbidities Based on Administrative Claims Data.

Linden, Thomas; De Jong, Johann; Lu, Chao; Kiri, Victor; Haeffs, Kathrin; Fröhlich, Holger

Linden, Thomas; De Jong, Johann; Lu, Chao; Kiri, Victor; Haeffs, Kathrin; Fröhlich, Holger.

Afiliação

Linden T; Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Schloss Birlinghoven, Sankt Augustin, Germany.
De Jong J; Bonn-Aachen International Center for Information Technology (B-IT), University of Bonn, Bonn, Germany.
Lu C; UCB Biosciences GmbH, Monheim, Germany.
Kiri V; UCB Biosciences GmbH, Monheim, Germany.
Haeffs K; UCB Ltd., Raleigh, NC, United States.
Fröhlich H; UCB Ltd., Raleigh, NC, United States.

Front Artif Intell ; 4: 610197, 2021.

Article em En | MEDLINE | ID: mdl-34095818

Palavras-chave

P4 medicine; administrative claims data; comorbidity prediction; epilepsy; machine learning; neural networks; personalized medicine; precision medicine

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article