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Advanced Data Analytics for Clinical Research Part I: What are the Tools?
Zhou, Nicolas; Corsini, Erin M; Jin, Shida; Barbosa, Gregory R; Kell, Trey; Antonoff, Michael H; Antonoff, Mara B.
Afiliação
  • Zhou N; 4002 Department of Thoracic and Cardiovascular Surgery, University of Texas MD Anderson Cancer Center, Houston, USA.
  • Corsini EM; 4002 Department of Thoracic and Cardiovascular Surgery, University of Texas MD Anderson Cancer Center, Houston, USA.
  • Jin S; 4002 Institutional Analytics and Informatics, University of Texas MD Anderson Cancer Center, Houston, USA.
  • Barbosa GR; 4002 Institutional Analytics and Informatics, University of Texas MD Anderson Cancer Center, Houston, USA.
  • Kell T; 4002 Institutional Analytics and Informatics, University of Texas MD Anderson Cancer Center, Houston, USA.
  • Antonoff MH; 3990 Jones Graduate School of Business, Rice University, Houston, USA.
  • Antonoff MB; 4002 Department of Thoracic and Cardiovascular Surgery, University of Texas MD Anderson Cancer Center, Houston, USA.
Innovations (Phila) ; 15(2): 114-119, 2020.
Article em En | MEDLINE | ID: mdl-32107958
ABSTRACT
The concept of Big Data is changing the way that clinical research can be performed. Cardiothoracic surgeons need to understand the dynamic digital transformation taking place in the healthcare industry. In the last decade, technological advances and Big Data analytics have become powerful tools for businesses. In healthcare, rapid expansion of Big Data infrastructure has occurred in parallel with attempts to reduce cost and improve outcomes. Many hospitals around the country are augmenting traditional relational databases with Big Data infrastructure. Advanced data capture and categorization tools such as natural language processing and optical character recognition are being developed for clinical and research use, while Internet of Things in the form of wearable technology serves as an additional source of data usable for research. As cardiothoracic surgeons seek ways to innovate, novel approaches to data acquisition and analysis enable a more rigorous level of investigatory efforts.
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Texto completo: 1 Eixos temáticos: Pesquisa_clinica Base de dados: MEDLINE Assunto principal: Processamento de Linguagem Natural / Setor de Assistência à Saúde / Mineração de Dados / Internet das Coisas Tipo de estudo: Guideline Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Eixos temáticos: Pesquisa_clinica Base de dados: MEDLINE Assunto principal: Processamento de Linguagem Natural / Setor de Assistência à Saúde / Mineração de Dados / Internet das Coisas Tipo de estudo: Guideline Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article