Artificial intelligence, diagnostic imaging and neglected tropical diseases: ethical implications
Artificial intelligence, defined as a system capable of interpreting and learning from data to produce a specific goal, has made significant advances in the field of neglected tropical diseases. Specifically, artificial intelligence is increasingly applied to the task of interpreting images of such...
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Veröffentlicht in: | Bulletin of the World Health Organization 2020-04, Vol.98 (4), p.288-289 |
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description | Artificial intelligence, defined as a system capable of interpreting and learning from data to produce a specific goal, has made significant advances in the field of neglected tropical diseases. Specifically, artificial intelligence is increasingly applied to the task of interpreting images of such diseases and generating accurate and reliable diagnoses that may ultimately inform management of these conditions. Neglected tropical diseases affect over a billion people globally and are a significant source of morbidity and mortality in low- and middle-income countries. Artificial intelligence has the potential to transform how such diseases are diagnosed and may contribute to enabling clinical and public health delivery in low- and middle-income countries. For example, artificial intelligence applied to neglected tropical disease diagnosis may help drive pointof-care clinical decision-making, identify outbreaks before they spread and help map these diseases to guide public health surveillance and control efforts. The latest research in this field demonstrates that novel diagnostic tools, such as mobile phone microscopes have rapidly improved diagnostic characteristics and broadened the scope of pathogens tested, and have excellent functionality in neglected tropical disease-endemic settings. Such devices are already being field tested and implemented on a limited scale, for example in Côte d'Ivoire. |
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Specifically, artificial intelligence is increasingly applied to the task of interpreting images of such diseases and generating accurate and reliable diagnoses that may ultimately inform management of these conditions. Neglected tropical diseases affect over a billion people globally and are a significant source of morbidity and mortality in low- and middle-income countries. Artificial intelligence has the potential to transform how such diseases are diagnosed and may contribute to enabling clinical and public health delivery in low- and middle-income countries. For example, artificial intelligence applied to neglected tropical disease diagnosis may help drive pointof-care clinical decision-making, identify outbreaks before they spread and help map these diseases to guide public health surveillance and control efforts. The latest research in this field demonstrates that novel diagnostic tools, such as mobile phone microscopes have rapidly improved diagnostic characteristics and broadened the scope of pathogens tested, and have excellent functionality in neglected tropical disease-endemic settings. Such devices are already being field tested and implemented on a limited scale, for example in Côte d'Ivoire.</description><identifier>ISSN: 0042-9686</identifier><identifier>EISSN: 1564-0604</identifier><identifier>DOI: 10.2471/BLF.19.237560</identifier><language>eng</language><publisher>Geneva: World Health Organization</publisher><subject>Artificial intelligence ; Cellular telephones ; Clinical decision making ; Consent ; Decision making ; Diagnostic systems ; Disease ; Diseases ; Ethics ; Health care ; Health surveillance ; High income ; Identity theft ; Industrialized nations ; Low income groups ; Medical diagnosis ; Microscopes ; Microscopy ; Mobile phones ; Morbidity ; Pathogens ; Personal information ; Product development ; Public health ; Stakeholders ; Surveillance ; Technological change ; Technology ; Tropical diseases</subject><ispartof>Bulletin of the World Health Organization, 2020-04, Vol.98 (4), p.288-289</ispartof><rights>Copyright World Health Organization Apr 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27845,27903,27904</link.rule.ids></links><search><creatorcontrib>Vaisman, Alon</creatorcontrib><creatorcontrib>Linder, Nina</creatorcontrib><creatorcontrib>Lundin, Johan</creatorcontrib><creatorcontrib>Orchanian-Cheff, Ani</creatorcontrib><creatorcontrib>Coulibaly, Jean T</creatorcontrib><creatorcontrib>Ephraim, Richard K D</creatorcontrib><creatorcontrib>Bogoch, Isaac I</creatorcontrib><title>Artificial intelligence, diagnostic imaging and neglected tropical diseases: ethical implications</title><title>Bulletin of the World Health Organization</title><description>Artificial intelligence, defined as a system capable of interpreting and learning from data to produce a specific goal, has made significant advances in the field of neglected tropical diseases. 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The latest research in this field demonstrates that novel diagnostic tools, such as mobile phone microscopes have rapidly improved diagnostic characteristics and broadened the scope of pathogens tested, and have excellent functionality in neglected tropical disease-endemic settings. 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subjects | Artificial intelligence Cellular telephones Clinical decision making Consent Decision making Diagnostic systems Disease Diseases Ethics Health care Health surveillance High income Identity theft Industrialized nations Low income groups Medical diagnosis Microscopes Microscopy Mobile phones Morbidity Pathogens Personal information Product development Public health Stakeholders Surveillance Technological change Technology Tropical diseases |
title | Artificial intelligence, diagnostic imaging and neglected tropical diseases: ethical implications |
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