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Can Artificial Intelligence Improve the Management of Pneumonia

The use of artificial intelligence (AI) to support clinical medical decisions is a rather promising concept. There are two important factors that have driven these advances: the availability of data from electronic health records (EHR) and progress made in computational performance. These two concep...

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Autores principales: Chumbita, Mariana, Cillóniz, Catia, Puerta-Alcalde, Pedro, Moreno-García, Estela, Sanjuan, Gemma, Garcia-Pouton, Nicole, Soriano, Alex, Torres, Antoni, Garcia-Vidal, Carolina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7019351/
https://www.ncbi.nlm.nih.gov/pubmed/31963480
http://dx.doi.org/10.3390/jcm9010248
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author Chumbita, Mariana
Cillóniz, Catia
Puerta-Alcalde, Pedro
Moreno-García, Estela
Sanjuan, Gemma
Garcia-Pouton, Nicole
Soriano, Alex
Torres, Antoni
Garcia-Vidal, Carolina
author_facet Chumbita, Mariana
Cillóniz, Catia
Puerta-Alcalde, Pedro
Moreno-García, Estela
Sanjuan, Gemma
Garcia-Pouton, Nicole
Soriano, Alex
Torres, Antoni
Garcia-Vidal, Carolina
author_sort Chumbita, Mariana
collection PubMed
description The use of artificial intelligence (AI) to support clinical medical decisions is a rather promising concept. There are two important factors that have driven these advances: the availability of data from electronic health records (EHR) and progress made in computational performance. These two concepts are interrelated with respect to complex mathematical functions such as machine learning (ML) or neural networks (NN). Indeed, some published articles have already demonstrated the potential of these approaches in medicine. When considering the diagnosis and management of pneumonia, the use of AI and chest X-ray (CXR) images primarily have been indicative of early diagnosis, prompt antimicrobial therapy, and ultimately, better prognosis. Coupled with this is the growing research involving empirical therapy and mortality prediction, too. Maximizing the power of NN, the majority of studies have reported high accuracy rates in their predictions. As AI can handle large amounts of data and execute mathematical functions such as machine learning and neural networks, AI can be revolutionary in supporting the clinical decision-making processes. In this review, we describe and discuss the most relevant studies of AI in pneumonia.
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spelling pubmed-70193512020-03-09 Can Artificial Intelligence Improve the Management of Pneumonia Chumbita, Mariana Cillóniz, Catia Puerta-Alcalde, Pedro Moreno-García, Estela Sanjuan, Gemma Garcia-Pouton, Nicole Soriano, Alex Torres, Antoni Garcia-Vidal, Carolina J Clin Med Review The use of artificial intelligence (AI) to support clinical medical decisions is a rather promising concept. There are two important factors that have driven these advances: the availability of data from electronic health records (EHR) and progress made in computational performance. These two concepts are interrelated with respect to complex mathematical functions such as machine learning (ML) or neural networks (NN). Indeed, some published articles have already demonstrated the potential of these approaches in medicine. When considering the diagnosis and management of pneumonia, the use of AI and chest X-ray (CXR) images primarily have been indicative of early diagnosis, prompt antimicrobial therapy, and ultimately, better prognosis. Coupled with this is the growing research involving empirical therapy and mortality prediction, too. Maximizing the power of NN, the majority of studies have reported high accuracy rates in their predictions. As AI can handle large amounts of data and execute mathematical functions such as machine learning and neural networks, AI can be revolutionary in supporting the clinical decision-making processes. In this review, we describe and discuss the most relevant studies of AI in pneumonia. MDPI 2020-01-17 /pmc/articles/PMC7019351/ /pubmed/31963480 http://dx.doi.org/10.3390/jcm9010248 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Chumbita, Mariana
Cillóniz, Catia
Puerta-Alcalde, Pedro
Moreno-García, Estela
Sanjuan, Gemma
Garcia-Pouton, Nicole
Soriano, Alex
Torres, Antoni
Garcia-Vidal, Carolina
Can Artificial Intelligence Improve the Management of Pneumonia
title Can Artificial Intelligence Improve the Management of Pneumonia
title_full Can Artificial Intelligence Improve the Management of Pneumonia
title_fullStr Can Artificial Intelligence Improve the Management of Pneumonia
title_full_unstemmed Can Artificial Intelligence Improve the Management of Pneumonia
title_short Can Artificial Intelligence Improve the Management of Pneumonia
title_sort can artificial intelligence improve the management of pneumonia
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7019351/
https://www.ncbi.nlm.nih.gov/pubmed/31963480
http://dx.doi.org/10.3390/jcm9010248
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