La inteligencia artificial y sus aplicaciones en medicina I: introducción antecedentes a la IA y robótica

Ávila-Tomás, José Francisco; Mayer, Miguel Ángel; Varela, Víctor Julio Quesada

doi:10.1016/j.aprim.2020.04.013

Cited by 35 publications

(18 citation statements)

References 23 publications

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“…Health technologies have advanced over the years [ 1 ]. Artificial Intelligence is a branch of computer science/engineering/technology that aims to develop computer systems to perform tasks that can be performed better by humans than by machines, or which do not have a viable algorithmic solution in conventional computing [ 2 ]. AI is used in medicine using computers that, by analyzing a large volume of information and following algorithms defined by experts, can propose solutions to medical problems [ 3 , 4 ].…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of Using the FreeStyle Libre® System for Monitoring Blood Glucose during the COVID-19 Pandemic in Diabetic Individuals: Systematic Review

et al. 2023

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Background: Artificial Intelligence (AI) is an area of computer science/engineering that is aiming to spread technological systems. The COVID-19 pandemic caused economic and public health turbulence around the world. Among the many possibilities for using AI in the medical field is FreeStyle Libre® (FSL), which uses a disposable sensor inserted into the user’s arm, and a touchscreen device/reader is used to scan and retrieve other continuous monitoring of glucose (CMG) readings. The aim of this systematic review is to summarize the effectiveness of FSL blood glucose monitoring during the COVID-19 pandemic. Methods: This systematic review was carried out in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) and was registered in the international prospective register of systematic reviews (PROSPERO: CRD42022340562). The inclusion criteria considered studies involving the use of the FSL device during the COVID-19 pandemic and published in English. No publication date restrictions were set. The exclusion criteria were abstracts, systematic reviews, studies with patients with other diseases, monitoring with other equipment, patients with COVID-19, and bariatrics patients. Seven databases were searched (PubMed, Scopus, Embase, Web of Science, Scielo, PEDro and Cochrane Library). The ACROBAT-NRSI tool (A Cochrane Risk of Bias Assessment Tool for Non-Randomized Studies) was used to evaluate the risk of bias in the selected articles. Results: A total of 113 articles were found. Sixty-four were excluded because they were duplicates, 39 were excluded after reading the titles and abstracts, and twenty articles were considered for full reading. Of the 10 articles analyzed, four articles were excluded because they did not meet the inclusion criteria. Thus, six articles were included in the current systematic review. It was observed that among the selected articles, only two were classified as having serious risk of bias. It was shown that FSL had a positive impact on glycemic control and on reducing the number of individuals with hypoglycemia. Conclusion: The findings suggest that the implementation of FSL during COVID-19 confinement in this population can be confidently stated to have been effective in diabetes mellitus patients.

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Section: Introductionmentioning

confidence: 99%

Effectiveness of Using the FreeStyle Libre® System for Monitoring Blood Glucose during the COVID-19 Pandemic in Diabetic Individuals: Systematic Review

et al. 2023

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“…The COVID-19 pandemic has given a boost to the research sector, favoring the integration of this technology in digital radiology [ 11 ]. Its applications in computed tomography/X-ray of the thorax seem to bring the moment of its introduction in the clinical routine [ 12 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

Impact of the Rise of Artificial Intelligence in Radiology: What Do Students Think?

Barreiro-Ares

Morales-Santiago

Portero

et al. 2023

IJERPH

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The rise of artificial intelligence (AI) in medicine, and particularly in radiology, is becoming increasingly prominent. Its impact will transform the way the specialty is practiced and the current and future education model. The aim of this study is to analyze the perception that undergraduate medical students have about the current situation of AI in medicine, especially in radiology. A survey with 17 items was distributed to medical students between 3 January to 31 March 2022. Two hundred and eighty-one students correctly responded the questionnaire; 79.3% of them claimed that they knew what AI is. However, their objective knowledge about AI was low but acceptable. Only 24.9% would choose radiology as a specialty, and only 40% of them as one of their first three options. The applications of this technology were valued positively by most students, who give it an important Support Role, without fear that the radiologist will be replaced by AI (79.7%). The majority (95.7%) agreed with the need to implement well-established ethical principles in AI, and 80% valued academic training in AI positively. Surveyed medical students have a basic understanding of AI and perceive it as a useful tool that will transform radiology.

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“…Como exemplo, é o fato de que a inteligência artificial na saúde pode atualizar dados em tempo real e constatar variáveis para calcular a necessidade de sistematização ou a necessidade de mais unidades, melhorando assim a gestão de leitos. Dessa forma, ações precoces podem ser tomadas para evitar o colapso das redes hospitalares, resolver problemas e prevenir complicações decorrentes da assistência (Tomás, 2020).…”

Section: Introductionunclassified

O uso da inteligência artificial na medicina: aplicações e benefícios

Soares

Araújo

Frazão

et al. 2023

RSD

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A realização deste estudo, justifica-se pela sua relevância acadêmica, científica e social, pautada em apresentar os avanços tecnológicos que envolvem a inteligência artificial na saúde. Dessa forma, o objetivo desta pesquisa incide em evidenciar as aplicações e benefícios da Inteligência Artificial na Medicina. Este estudo foi realizado por meio de uma revisão integrativa da literatura, de abordagem exploratória, cujo instituto, se resumiu em investigar, através de artigos já publicados, informações relevantes que respondessem à pergunta norteadora. Assim, o levantamento de dados ocorreu nas bases científicas: SCIELO e LILACS. As evidências apontam que o poder de processamento de dados da inteligência artificial na medicina é amplo. Um dos principais usos desse tipo de ferramenta é armazenar e processar dados com precisão. Isso permite que todos os arquivos sejam digitalizados, tornando-os mais fáceis de organizar, proteger e acessar. Não é apenas armazenamento, é uma maneira mais organizada de encontrar informações. Dependendo da necessidade de cada médico, algumas tecnologias podem acessar os dados mais relevantes para análises específicas, como resultados de exames ou adequação de tratamentos. Frente ao exposto, conhecendo os benefícios da IA, vale ressaltar que nenhuma das tecnologias mencionadas substitui o papel do médico. Pelo contrário, eles apenas contribuem para melhores decisões e facilitam o relacionamento com os pacientes. De qualquer forma, “não há dúvida de que a inteligência artificial permanecerá na medicina e continuará dando grandes passos no futuro”.

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La inteligencia artificial y sus aplicaciones en medicina I: introducción antecedentes a la IA y robótica

Cited by 35 publications

References 23 publications

Effectiveness of Using the FreeStyle Libre® System for Monitoring Blood Glucose during the COVID-19 Pandemic in Diabetic Individuals: Systematic Review

Effectiveness of Using the FreeStyle Libre® System for Monitoring Blood Glucose during the COVID-19 Pandemic in Diabetic Individuals: Systematic Review

Impact of the Rise of Artificial Intelligence in Radiology: What Do Students Think?

O uso da inteligência artificial na medicina: aplicações e benefícios

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