Big and deep hype and hope: on the special issue for deep learning and big data in healthcare

Rojo Álvarez, José Luis (2019). Big and deep hype and hope: on the special issue for deep learning and big data in healthcare. "Applied Sciences", v. 9 (n. 20); pp. 4452-4457. ISSN 2076-3417. https://doi.org/10.3390/app9204452.

Description

Title: Big and deep hype and hope: on the special issue for deep learning and big data in healthcare
Author/s:
  • Rojo Álvarez, José Luis
Item Type: Article
Título de Revista/Publicación: Applied Sciences
Date: 2019
ISSN: 2076-3417
Volume: 9
Subjects:
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Deep Learning networks are revolutionizing both the academic and the industrial scenarios of information and communication technologies. Their theoretical maturity and the coexistence of large datasets with computational media is making this technology available to a wide community of makers and users, and recent evolution has been remarkable in techniques such as deep belief networks, Boltzmann machines, auto encoders, or recurrent networks. In a different yet often closely related arena, the analysis of large amounts of data from the Electronic Health Recording, the Hospital Information Systems, and other medical data sources, success cases on companies, and new products have made possible new tools for estimation of in-hospital stay duration, chronic patient identification, and policies to reduce readmissions by preventing illness progression. Large and small companies have paid attention to this new era, in which machine learning and statistical analysis need to be revisited if they want to provide suitable algorithms, especially in healthcare scenarios, where patient data more than ever is becoming the key to improving patient healthcare.

More information

Item ID: 67114
DC Identifier: https://oa.upm.es/67114/
OAI Identifier: oai:oa.upm.es:67114
DOI: 10.3390/app9204452
Official URL: https://www.mdpi.com/2076-3417/9/20/4452
Deposited by: Memoria Investigacion
Deposited on: 18 May 2021 07:37
Last Modified: 18 May 2021 07:37
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