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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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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. |
format | Online Article Text |
id | pubmed-7019351 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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