Exponential growth of systematic reviews assessing artificial intelligence studies in medicine: challenges and opportunities

The evidence-based medicine (EBM) movement is stepping up its efforts to assess medical artificial intelligence (AI) and data science studies. Since 2017, there has been a marked increase in the number of published systematic reviews that assess medical AI studies. Increasingly, data from observatio...

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Autores principales: von Groote, Thilo, Ghoreishi, Narges, Björklund, Maria, Porschen, Christian, Puljak, Livia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Letter
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9238033/
https://www.ncbi.nlm.nih.gov/pubmed/35761303
http://dx.doi.org/10.1186/s13643-022-01984-7
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author von Groote, Thilo
Ghoreishi, Narges
Björklund, Maria
Porschen, Christian
Puljak, Livia
author_facet von Groote, Thilo
Ghoreishi, Narges
Björklund, Maria
Porschen, Christian
Puljak, Livia
author_sort von Groote, Thilo
collection PubMed
description The evidence-based medicine (EBM) movement is stepping up its efforts to assess medical artificial intelligence (AI) and data science studies. Since 2017, there has been a marked increase in the number of published systematic reviews that assess medical AI studies. Increasingly, data from observational studies are used in systematic reviews of medical AI studies. Assessment of risk of bias is especially important in medical AI studies to detect possible “AI bias”. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13643-022-01984-7.
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spelling pubmed-92380332022-06-29 Exponential growth of systematic reviews assessing artificial intelligence studies in medicine: challenges and opportunities von Groote, Thilo Ghoreishi, Narges Björklund, Maria Porschen, Christian Puljak, Livia Syst Rev Letter The evidence-based medicine (EBM) movement is stepping up its efforts to assess medical artificial intelligence (AI) and data science studies. Since 2017, there has been a marked increase in the number of published systematic reviews that assess medical AI studies. Increasingly, data from observational studies are used in systematic reviews of medical AI studies. Assessment of risk of bias is especially important in medical AI studies to detect possible “AI bias”. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13643-022-01984-7. BioMed Central 2022-06-28 /pmc/articles/PMC9238033/ /pubmed/35761303 http://dx.doi.org/10.1186/s13643-022-01984-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Letter
von Groote, Thilo
Ghoreishi, Narges
Björklund, Maria
Porschen, Christian
Puljak, Livia
Exponential growth of systematic reviews assessing artificial intelligence studies in medicine: challenges and opportunities
title Exponential growth of systematic reviews assessing artificial intelligence studies in medicine: challenges and opportunities
title_full Exponential growth of systematic reviews assessing artificial intelligence studies in medicine: challenges and opportunities
title_fullStr Exponential growth of systematic reviews assessing artificial intelligence studies in medicine: challenges and opportunities
title_full_unstemmed Exponential growth of systematic reviews assessing artificial intelligence studies in medicine: challenges and opportunities
title_short Exponential growth of systematic reviews assessing artificial intelligence studies in medicine: challenges and opportunities
title_sort exponential growth of systematic reviews assessing artificial intelligence studies in medicine: challenges and opportunities
topic Letter
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9238033/
https://www.ncbi.nlm.nih.gov/pubmed/35761303
http://dx.doi.org/10.1186/s13643-022-01984-7
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