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Artificial intelligence in health care: laying the Foundation for Responsible, sustainable, and inclusive innovation in low- and middle-income countries
The World Health Organization and other institutions are considering Artificial Intelligence (AI) as a technology that can potentially address some health system gaps, especially the reduction of global health inequalities in low- and middle-income countries (LMICs). However, because most AI-based h...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7315549/ https://www.ncbi.nlm.nih.gov/pubmed/32580741 http://dx.doi.org/10.1186/s12992-020-00584-1 |
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author | Alami, Hassane Rivard, Lysanne Lehoux, Pascale Hoffman, Steven J. Cadeddu, Stéphanie Bernadette Mafalda Savoldelli, Mathilde Samri, Mamane Abdoulaye Ag Ahmed, Mohamed Ali Fleet, Richard Fortin, Jean-Paul |
author_facet | Alami, Hassane Rivard, Lysanne Lehoux, Pascale Hoffman, Steven J. Cadeddu, Stéphanie Bernadette Mafalda Savoldelli, Mathilde Samri, Mamane Abdoulaye Ag Ahmed, Mohamed Ali Fleet, Richard Fortin, Jean-Paul |
author_sort | Alami, Hassane |
collection | PubMed |
description | The World Health Organization and other institutions are considering Artificial Intelligence (AI) as a technology that can potentially address some health system gaps, especially the reduction of global health inequalities in low- and middle-income countries (LMICs). However, because most AI-based health applications are developed and implemented in high-income countries, their use in LMICs contexts is recent and there is a lack of robust local evaluations to guide decision-making in low-resource settings. After discussing the potential benefits as well as the risks and challenges raised by AI-based health care, we propose five building blocks to guide the development and implementation of more responsible, sustainable, and inclusive AI health care technologies in LMICs. |
format | Online Article Text |
id | pubmed-7315549 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-73155492020-06-25 Artificial intelligence in health care: laying the Foundation for Responsible, sustainable, and inclusive innovation in low- and middle-income countries Alami, Hassane Rivard, Lysanne Lehoux, Pascale Hoffman, Steven J. Cadeddu, Stéphanie Bernadette Mafalda Savoldelli, Mathilde Samri, Mamane Abdoulaye Ag Ahmed, Mohamed Ali Fleet, Richard Fortin, Jean-Paul Global Health Debate The World Health Organization and other institutions are considering Artificial Intelligence (AI) as a technology that can potentially address some health system gaps, especially the reduction of global health inequalities in low- and middle-income countries (LMICs). However, because most AI-based health applications are developed and implemented in high-income countries, their use in LMICs contexts is recent and there is a lack of robust local evaluations to guide decision-making in low-resource settings. After discussing the potential benefits as well as the risks and challenges raised by AI-based health care, we propose five building blocks to guide the development and implementation of more responsible, sustainable, and inclusive AI health care technologies in LMICs. BioMed Central 2020-06-24 /pmc/articles/PMC7315549/ /pubmed/32580741 http://dx.doi.org/10.1186/s12992-020-00584-1 Text en © The Author(s) 2020 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/. The Creative Commons Public Domain Dedication waiver (http://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 | Debate Alami, Hassane Rivard, Lysanne Lehoux, Pascale Hoffman, Steven J. Cadeddu, Stéphanie Bernadette Mafalda Savoldelli, Mathilde Samri, Mamane Abdoulaye Ag Ahmed, Mohamed Ali Fleet, Richard Fortin, Jean-Paul Artificial intelligence in health care: laying the Foundation for Responsible, sustainable, and inclusive innovation in low- and middle-income countries |
title | Artificial intelligence in health care: laying the Foundation for Responsible, sustainable, and inclusive innovation in low- and middle-income countries |
title_full | Artificial intelligence in health care: laying the Foundation for Responsible, sustainable, and inclusive innovation in low- and middle-income countries |
title_fullStr | Artificial intelligence in health care: laying the Foundation for Responsible, sustainable, and inclusive innovation in low- and middle-income countries |
title_full_unstemmed | Artificial intelligence in health care: laying the Foundation for Responsible, sustainable, and inclusive innovation in low- and middle-income countries |
title_short | Artificial intelligence in health care: laying the Foundation for Responsible, sustainable, and inclusive innovation in low- and middle-income countries |
title_sort | artificial intelligence in health care: laying the foundation for responsible, sustainable, and inclusive innovation in low- and middle-income countries |
topic | Debate |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7315549/ https://www.ncbi.nlm.nih.gov/pubmed/32580741 http://dx.doi.org/10.1186/s12992-020-00584-1 |
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