{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["16(1)"],"submitter":["Alami H"],"pubmed_abstract":["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."],"journal":["Globalization and health"],"pagination":["52"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC7315549"],"repository":["biostudies-literature"],"pubmed_title":["Artificial intelligence in health care: laying the Foundation for Responsible, sustainable, and inclusive innovation in low- and middle-income countries."],"pmcid":["PMC7315549"],"pubmed_authors":["Alami H","Cadeddu SBM","Savoldelli M","Ag Ahmed MA","Hoffman SJ","Rivard L","Lehoux P","Samri MA","Fortin JP","Fleet R"],"additional_accession":[]},"is_claimable":false,"name":"Artificial intelligence in health care: laying the Foundation for Responsible, sustainable, and inclusive innovation in low- and middle-income countries.","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.","dates":{"release":"2020-01-01T00:00:00Z","publication":"2020 Jun","modification":"2020-07-02T07:05:49Z","creation":"2020-07-02T07:05:49Z"},"accession":"S-EPMC7315549","cross_references":{"pubmed":["32580741"],"doi":["10.1186/s12992-020-00584-1 "]}}