Identifying Ethical Considerations for Machine Learning Healthcare Applications.
Along with potential benefits to healthcare delivery, machine learning healthcare applications (ML-HCAs) raise a number of ethical concerns. Ethical evaluations of ML-HCAs will need to structure the overall problem of evaluating these technologies, especially for a diverse group of stakeholders. Thi...
| Publicado en: | American Journal of Bioethics Vol. 20; no. 11; pp. 7 - 18 |
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| Autores principales: | , , |
| Formato: | review tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Nov2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=146630565&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 146630565 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15265161 FKZ jtl: American Journal of Bioethics issn: 15265161 maglogo: N pubinfo: dt: Nov2020 vid: 20 iid: 11 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 146630565 146630565 146630565 10.1080/15265161.2020.1819469 146630565 ppf: 7 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Identifying Ethical Considerations for Machine Learning Healthcare Applications. aug: au: Char, Danton S. Abràmoff, Michael D. Feudtner, Chris affil: Stanford University School of Medicine sug: subj: Machine Learning Ethical Issues Artificial Intelligence Health Care Delivery Neural Networks (Computer) Algorithms Technology Medical Informatics Patient Safety Conceptual Framework ab: Along with potential benefits to healthcare delivery, machine learning healthcare applications (ML-HCAs) raise a number of ethical concerns. Ethical evaluations of ML-HCAs will need to structure the overall problem of evaluating these technologies, especially for a diverse group of stakeholders. This paper outlines a systematic approach to identifying ML-HCA ethical concerns, starting with a conceptual model of the pipeline of the conception, development, implementation of ML-HCAs, and the parallel pipeline of evaluation and oversight tasks at each stage. Over this model, we layer key questions that raise value-based issues, along with ethical considerations identified in large part by a literature review, but also identifying some ethical considerations that have yet to receive attention. This pipeline model framework will be useful for systematic ethical appraisals of ML-HCA from development through implementation, and for interdisciplinary collaboration of diverse stakeholders that will be required to understand and subsequently manage the ethical implications of ML-HCAs. pubtype: Academic Journal doctype: review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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