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Artificial intelligence in pulmonary medicine: computer vision, predictive model and COVID-19.
Khemasuwan, Danai; Sorensen, Jeffrey S; Colt, Henri G.
Afiliação
  • Khemasuwan D; Division of Pulmonary and Critical Care Medicine, Virginia Commonwealth University, Richmond, VA, USA danai.khemasuwan@vcuhealth.org.
  • Sorensen JS; nuBlu, Salt Lake City, UT, USA.
  • Colt HG; Division of Pulmonary and Critical Care Medicine, University of California Irvine, Irvine, CA, USA.
Eur Respir Rev ; 29(157)2020 Sep 30.
Article em En | MEDLINE | ID: mdl-33004526
ABSTRACT
Artificial intelligence (AI) is transforming healthcare delivery. The digital revolution in medicine and healthcare information is prompting a staggering growth of data intertwined with elements from many digital sources such as genomics, medical imaging and electronic health records. Such massive growth has sparked the development of an increasing number of AI-based applications that can be deployed in clinical practice. Pulmonary specialists who are familiar with the principles of AI and its applications will be empowered and prepared to seize future practice and research opportunities. The goal of this review is to provide pulmonary specialists and other readers with information pertinent to the use of AI in pulmonary medicine. First, we describe the concept of AI and some of the requisites of machine learning and deep learning. Next, we review some of the literature relevant to the use of computer vision in medical imaging, predictive modelling with machine learning, and the use of AI for battling the novel severe acute respiratory syndrome-coronavirus-2 pandemic. We close our review with a discussion of limitations and challenges pertaining to the further incorporation of AI into clinical pulmonary practice.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Pneumonia Viral / Algoritmos / Inteligência Artificial / Pneumologia / Infecções por Coronavirus / Atenção à Saúde / Aprendizado de Máquina / Betacoronavirus Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Eur Respir Rev Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Pneumonia Viral / Algoritmos / Inteligência Artificial / Pneumologia / Infecções por Coronavirus / Atenção à Saúde / Aprendizado de Máquina / Betacoronavirus Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Eur Respir Rev Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos