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Current Women`s Health Reviews

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ISSN (Print): 1573-4048
ISSN (Online): 1875-6581

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Editorial

Women’s Health and Artificial Intelligence (AI): Addressing Potential for Bias and Discrimination in AI

Author(s): John Yeh and Camille A. Clare

Volume 19, Issue 4, 2023

Published on: 01 March, 2023

Article ID: e010323214222 Pages: 2

DOI: 10.2174/157340481904230301140515

[1]
Dimitrov DV. Medical Internet of Things and Big Data in Healthcare. Healthc Inform Res 2016 Jul; 22(3): 156-63.Epub 2016 Jul 31.
[http://dx.doi.org/10.4258/hir.2016.22.3.156.] [PMID: 27525156] [PMCID: PMC4981575]
[2]
Briganti G, and Le Moine O. Artificial Intelligence in Medicine: Today and Tomorrow. Front Med 2020; 7: 27.
[http://dx.doi.org/10.3389/fmed.2020.00027]
[3]
Crigger E, Reinbold K, Hanson C, et al. Trustworthy Augmented Intelligence in Health Care. J Med Syst 46: 12.(2022)
[http://dx.doi.org/10.1007/s10916-021-01790-z]
[4]
Dhombres F, Bonnard J, Bailly K, Maurice P, Papageorghiou AT, Jouannic JM. Contributions of Artificial Intelligence Reported in Obstetrics and Gynecology Journals: Systematic Review. J Med Internet Res 2022 Apr 20; 24(4)e35465
[http://dx.doi.org/10.2196/35465] [PMID: 35297766] [PMCID: PMC9069308]
[5]
Islam MN, Mustafina SN, Mahmud T, et al. Machine learning to predict pregnancy outcomes: a systematic review, synthesizing framework and future research agenda. BMC Pregnancy Childbirth 22: 348.(2022)
[http://dx.doi.org/10.1186/s12884-022-04594-2]
[6]
Barbounaki S, Vivilaki VG. Intelligent systems in obstetrics and midwifery: Applications of machine learning Eur J Midwifery 2021 Dec 20; 5: 58.
[http://dx.doi.org/10.18332/ejm/143166] [PMID: 35005483] [PMCID: PMC8686058]
[7]
Wang R, Pan W, Jin L, et al. Artificial intelligence in reproductive medicine. Reproduction 2019 Oct; 158(4): R139-54.
[http://dx.doi.org/10.1530/REP-18-0523] [PMID: 30970326] [PMCID: PMC6733338]
[8]
Yoldemir T. Artificial intelligence and women's health. Climacteric 2020 Feb; 23(1): 1-2.
[http://dx.doi.org/10.1080/13697137.2019.1682804.] [PMID: 31951763]
[9]
Stahl BC, Schroeder D, Rodrigues R. (2023) Unfair and Illegal Discrimination. Ethics of Artificial Intelligence SpringerBriefs in Research and Innovation Governance Springer, Cham.
[http://dx.doi.org/10.1007/978-3-031-17040-9_2]
[10]
Oswald M, Grace J, Urwin S, Barnes GC. (2018) Algorithmic risk assessment policing models: lessons from the Durham HART model and ‘Experimental’ proportionality Information & Communications Technology Law 27:2: 223-50.
[http://dx.doi.org/10.1080/13600834.2018.1458455]
[11]
Gichoya JW, Banerjee I, Bhimireddy AR, et al. AI recognition of patient race in medical imaging: a modelling study. Lancet Digit Health 2022 jun; 4(6): e406-14. Epub 2022 May 11.
[http://dx.doi.org/10.1016/S25897500(22)00063-2.] [PMID: 35568690] [PMCID: PMC9650160]
[12]
Obermeyer Z, Powers B, Vogeli C, Mullainathan S. Dissecting racial bias in an algorithm used to manage the health of populations Science. 2019 Oct 25; 366(6464): 447-53.
[http://dx.doi.org/10.1126/science.aax2342] [PMID: 31649194]
[13]
Rubashkin N. Why Equitable Access to Vaginal Birth Requires Abolition of Race-Based Medicine. AMA J Ethics 2022; 24(3): E233-8.
[http://dx.doi.org/10.1001/amajethics.2022.233.]
[14]
Collett , Clementine and Dillon , Sarah . (2019) AI and Gender: Four Proposals for Future Research. Cambridge: The Leverhulme Centre for the Future of Intelligence.
[15]
Clarke R. Principles and business processes for responsible AI, Computer Law & Security Review 2019; 35(4): 410-22. ISSN 0267-3649
[http://dx.doi.org/10.1016/j.clsr.2019.04.007]
[16]
Truby J, Brown R, Ibrahim I, & Parellada O. (2022) A Sandbox Approach to Regulating High-Risk Artificial Intelligence Applications. European Journal of Risk Regulation 13(2): 270-94.
[http://dx.doi.org/10.1017/err.2021.52]
[17]
Sun N, Esom K, Dhaliwal M, Amon JJ. Human Rights and Digital Health Technologies. Health Hum Rights 2020 Dec; 22(2): 21-32.
[PMID: 33390689] [PMCID: PMC7762914]
[18]
Stix C. Actionable Principles for Artificial Intelligence Policy Three Pathways Sci Eng Ethics 2021 Feb 19; 27(1): 15.
[http://dx.doi.org/10.1007/s11948-020-00277-3.] [PMID: 33608756] [PMCID: PMC7895786]
[19]
US Department of Health and Human Services Artificial Intelligence (AI) Strategy January 2021. https://www.hhs.gov/sites/default/files/final-hhs-ai-strategy.pdf Accessed December 15, 2022.
[20]
The White House Blueprint for an AI Bill of Rights October 2022. https://www.whitehouse.gov/wp-content/uploads/2022/10/Blueprint-for-an-AI-Bill-of-Rights.pdfAccessed December 15, 2022
[21]
Clare CA. (2022) Race as a social construct should not be cited as a risk factor for postpartum preeclampsia. American journal of obstetrics and gynecology 227(2): 357-8.
[http://dx.doi.org/10.1016/j.ajog.2022.03.010]
[22]
Steinberg JR, Turner BE, DiTosto JD, et al. Race and Ethnicity Reporting and Representation in Obstetrics and Gynecology Clinical Trials and Publications From 2007-2020.JAMA Surg Published online December 21, 2022
[http://dx.doi.org/10.1001/jamasurg.2022.6600]
[23]
O’Brien J, Clare CA. (2022) Race-based Versus Race-conscious Medicine in Obstetrics and Gynecology. Clinical obstetrics and gynecology, 10.1097/GRF.0000000000000756. Advance online publication
[http://dx.doi.org/10.1097/GRF.0000000000000756]

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