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Big data and machine learning in critical care: Opportunities for collaborative research

Núñez Reiz, Antonio, MD ; Martínez Sagasti, Fernando, MD PhD ; Álvarez González, Manuel, MD PhD ; Blesa Malpica, Antonio, MD PhD ; Martín Benítez, Juan Carlos, MD PhD ; Nieto Cabrera, Mercedes, MD PhD ; del Pino Ramírez, Ángela, MD ; Gil Perdomo, José Miguel, MD ; Prada Alonso, Jesús ; Celi, Leo Anthony, MD MS MPH ; Armengol de la Hoz, Miguel Ángel, MBE ; Deliberato, Rodrigo, MD PhD ; Paik, Kenneth, MD MS MBA ; Pollard, Tom, PhD ; Raffa, Jesse, PhD ; Torres, Felipe ; Mayol, Julio, MD PhD ; Chafer, Joan, MD ; González Ferrer, Arturo, PhD ; Rey, Ángel ; González Luengo, Henar ; Fico, Giuseppe, PhD ; Lombroni, Ivana, MsC ; Hernandez, Liss, MsC ; López, Laura, MsC ; Merino, Beatriz, MsC ; Cabrera, María Fernanda, PhD ; Arredondo, María Teresa, PhD ; Bodí, María, MD PhD ; Gómez, Josep, PhD ; Rodríguez, Alejandro, MD PhD ; Sánchez García, Miguel, MD PhD

Medicina intensiva, 2019-01, Vol.43 (1), p.52-57 [Periódico revisado por pares]

Spain: Elsevier España, S.L.U

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Título:
Big data and machine learning in critical care: Opportunities for collaborative research
Autor: Núñez Reiz, Antonio, MD ; Martínez Sagasti, Fernando, MD PhD ; Álvarez González, Manuel, MD PhD ; Blesa Malpica, Antonio, MD PhD ; Martín Benítez, Juan Carlos, MD PhD ; Nieto Cabrera, Mercedes, MD PhD ; del Pino Ramírez, Ángela, MD ; Gil Perdomo, José Miguel, MD ; Prada Alonso, Jesús ; Celi, Leo Anthony, MD MS MPH ; Armengol de la Hoz, Miguel Ángel, MBE ; Deliberato, Rodrigo, MD PhD ; Paik, Kenneth, MD MS MBA ; Pollard, Tom, PhD ; Raffa, Jesse, PhD ; Torres, Felipe ; Mayol, Julio, MD PhD ; Chafer, Joan, MD ; González Ferrer, Arturo, PhD ; Rey, Ángel ; González Luengo, Henar ; Fico, Giuseppe, PhD ; Lombroni, Ivana, MsC ; Hernandez, Liss, MsC ; López, Laura, MsC ; Merino, Beatriz, MsC ; Cabrera, María Fernanda, PhD ; Arredondo, María Teresa, PhD ; Bodí, María, MD PhD ; Gómez, Josep, PhD ; Rodríguez, Alejandro, MD PhD ; Sánchez García, Miguel, MD PhD
Assuntos: Artificial intelligence ; Bases de datos clínicos ; Big data ; Clinical databases ; Collaborative work ; Critical Care ; Datathon ; Inteligencia artificial ; Machine learning ; MIMIC III ; Trabajo colaborativo
É parte de: Medicina intensiva, 2019-01, Vol.43 (1), p.52-57
Notas: ObjectType-Conference-1
SourceType-Conference Papers & Proceedings-1
content type line 25
Descrição: AbstractThe introduction of clinical information systems (CIS) in Intensive Care Units (ICUs) offers the possibility of storing a huge amount of machine-ready clinical data that can be used to improve patient outcomes and the allocation of resources, as well as suggest topics for randomized clinical trials. Clinicians, however, usually lack the necessary training for the analysis of large databases. In addition, there are issues referred to patient privacy and consent, and data quality. Multidisciplinary collaboration among clinicians, data engineers, machine-learning experts, statisticians, epidemiologists and other information scientists may overcome these problems.A multidisciplinary event (Critical Care Datathon) was held in Madrid (Spain) from 1 to 3 December 2017. Under the auspices of the Spanish Critical Care Society (SEMICYUC), the event was organized by the Massachusetts Institute of Technology (MIT) Critical Data Group (Cambridge, MA, USA), the Innovation Unit and Critical Care Department of San Carlos Clinic Hospital, and the Life Supporting Technologies group of Madrid Polytechnic University. After presentations referred to big data in the critical care environment, clinicians, data scientists and other health data science enthusiasts and lawyers worked in collaboration using an anonymized database (MIMIC III). Eight groups were formed to answer different clinical research questions elaborated prior to the meeting.The event produced analyses for the questions posed and outlined several future clinical research opportunities. Foundations were laid to enable future use of ICU databases in Spain, and a timeline was established for future meetings, as an example of how big data analysis tools have tremendous potential in our field.
Editor: Spain: Elsevier España, S.L.U
Idioma: Inglês;Espanhol

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Big data and machine learning in critical care: Opportunities for collaborative research

Spain: Elsevier España, S.L.U

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