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The value of standa...
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Arora, AnmolUniv Cambridge, England
(author)
The value of standards for health datasets in artificial intelligence-based applications
- Article/chapterEnglish2023
Publisher, publication year, extent ...
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NATURE PORTFOLIO,2023
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electronicrdacarrier
Numbers
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LIBRIS-ID:oai:DiVA.org:liu-199109
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https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-199109URI
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https://doi.org/10.1038/s41591-023-02608-wDOI
Supplementary language notes
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Language:English
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Summary in:English
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Subject category:ref swepub-contenttype
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Subject category:art swepub-publicationtype
Notes
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Funding Agencies|This project is funded by the NHS AI Lab at the NHS Transformation Directorate and The Health Foundation and managed by the National Institute for Health and Care Research (AI_HI200014). The views expressed in this publication are those of the author(s) an; NHS AI Lab at the NHS Transformation Directorate [AI_HI200014]; Health Foundation [104687]; National Pathology Imaging Co-operative, NPIC; Data to Early Diagnosis and Precision Medicine strand of the governments Industrial Strategy Challenge Fund; National Institutes of Health Research (NIHR) [AI_HI200014] Funding Source: National Institutes of Health Research (NIHR)
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Artificial intelligence as a medical device is increasingly being applied to healthcare for diagnosis, risk stratification and resource allocation. However, a growing body of evidence has highlighted the risk of algorithmic bias, which may perpetuate existing health inequity. This problem arises in part because of systemic inequalities in dataset curation, unequal opportunity to participate in research and inequalities of access. This study aims to explore existing standards, frameworks and best practices for ensuring adequate data diversity in health datasets. Exploring the body of existing literature and expert views is an important step towards the development of consensus-based guidelines. The study comprises two parts: a systematic review of existing standards, frameworks and best practices for healthcare datasets; and a survey and thematic analysis of stakeholder views of bias, health equity and best practices for artificial intelligence as a medical device. We found that the need for dataset diversity was well described in literature, and experts generally favored the development of a robust set of guidelines, but there were mixed views about how these could be implemented practically. The outputs of this study will be used to inform the development of standards for transparency of data diversity in health datasets (the STANDING Together initiative). A systematic review, combined with a stakeholder survey, presents an overview of current practices and recommendations for dataset curation in health, with specific focuses on data diversity and artificial intelligence-based applications.
Subject headings and genre
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Alderman, Joseph E.Univ Birmingham, England; Univ Hosp Birmingham NHS Fdn Trust, England; Univ Birmingham, England; Univ Birmingham, England
(author)
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Palmer, JoanneUniv Hosp Birmingham NHS Fdn Trust, England; Univ Birmingham, England; Univ Birmingham, England
(author)
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Ganapathi, ShaswathSandwell & West Birmingham Hosp NHS Trust, England
(author)
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Laws, ElinorUniv Birmingham, England; Univ Hosp Birmingham NHS Fdn Trust, England; Univ Birmingham, England; Univ Birmingham, England
(author)
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Mccradden, Melissa D.Hosp Sick Children, Canada; Peter Gilgan Ctr Res & Learning, Canada; Dalla Lana Sch Publ Hlth, Canada
(author)
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Oakden-Rayner, LaurenUniv Adelaide, Australia
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Pfohl, Stephen R.Google Res, CA USA
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Ghassemi, MarzyehMIT, MA USA; Inst Med Engn & Sci, MA USA; Vector Inst, Canada
(author)
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Mckay, FrancisUniv Oxford, England
(author)
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Treanor, DarrenLinköpings universitet,Avdelningen för inflammation och infektion,Medicinska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV,Region Östergötland, Klinisk patologi,Leeds Teaching Hosp NHS Trust, England; Univ Leeds, England(Swepub:liu)dartr72
(author)
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Rostamzadeh, NegarGoogle Res, Canada
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Mateen, BilalUCL, England; Wellcome Trust Res Labs, England
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Gath, JacquiSTANDING Together, England
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Adebajo, Adewole O.STANDING Together, England
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Kuku, StephanieUCL, England
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Matin, RubetaOxford Univ Hosp NHS Fdn Trust, England
(author)
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Heller, KatherineGoogle Res, CA USA
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Sapey, ElizabethUniv Birmingham, England; Univ Hosp Birmingham NHS Fdn Trust, England; Univ Birmingham, England; Univ Birmingham, England; Univ Birmingham, England
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Sebire, Neil J.Great Ormond St Hosp Biomed Res Ctr, England; Univ Hosp London, England
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Cole-Lewis, HeatherGoogle Res, CA USA
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Calvert, MelanieUniv Birmingham, England; Univ Birmingham, England; Univ Birmingham, England; Univ Birmingham, England; Univ Birmingham, England; Univ Birmingham, England; Univ Birmingham, England; Univ Birmingham, England; Univ Birmingham, England
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Denniston, AlastairUniv Birmingham, England; Univ Hosp Birmingham NHS Fdn Trust, England; Univ Birmingham, England; Univ Birmingham, England; Univ Birmingham, England; UCL, England; UCL, England
(author)
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Liu, XiaoxuanUniv Birmingham, England; Univ Hosp Birmingham NHS Fdn Trust, England; Univ Birmingham, England; Univ Birmingham, England
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Univ Cambridge, EnglandUniv Birmingham, England; Univ Hosp Birmingham NHS Fdn Trust, England; Univ Birmingham, England; Univ Birmingham, England
(creator_code:org_t)
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In:Nature Medicine: NATURE PORTFOLIO29, s. 2929-29381078-89561546-170X
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Arora, Anmol
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Alderman, Joseph ...
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Palmer, Joanne
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Ganapathi, Shasw ...
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Mccradden, Melis ...
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Oakden-Rayner, L ...
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Pfohl, Stephen R ...
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Mckay, Francis
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Treanor, Darren
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Rostamzadeh, Neg ...
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Mateen, Bilal
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Gath, Jacqui
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Adebajo, Adewole ...
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Kuku, Stephanie
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Matin, Rubeta
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Heller, Katherin ...
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Sapey, Elizabeth
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Sebire, Neil J.
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Cole-Lewis, Heat ...
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Calvert, Melanie
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Denniston, Alast ...
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Liu, Xiaoxuan
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