FedSepsis: A Federated Multi-Modal Deep Learning-Based Internet of Medical Things Application for Early Detection of Sepsis from Electronic Health Records Using Raspberry Pi and Jetson Nano Devices.

Alam, Mahbub Ul; Rahmani, Rahim

Alam, Mahbub Ul; Rahmani, Rahim.

Afiliación

Alam MU; Department of Computer and Systems Sciences, Stockholm University, 16407 Stockholm, Sweden.
Rahmani R; Department of Computer and Systems Sciences, Stockholm University, 16407 Stockholm, Sweden.

Sensors (Basel) ; 23(2)2023 Jan 14.

Article en En | MEDLINE | ID: mdl-36679766

Asunto(s)

Aprendizaje Profundo; Sepsis; Humanos; Registros Electrónicos de Salud; Aprendizaje Automático; Internet; Sepsis/diagnóstico

Palabras clave

Internet of Medical Things; clinical decision support system; deep learning; early sepsis detection; electronic health records; federated learning; multi-modality; natural language processing; smart healthcare

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Sepsis / Aprendizaje Profundo Tipo de estudio: Diagnostic_studies / Prognostic_studies / Screening_studies Límite: Humans Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Suecia Pais de publicación: Suiza

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