Prudently Evaluating Medical Adaptive Machine Learning Systems.
| Published in: | American Journal of Bioethics Vol. 24; no. 10; pp. 76 - 80 |
|---|---|
| Main Author: | |
| Format: | commentary Journal Article |
| Published: |
Taylor & Francis Ltd
Oct2024
|
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=179686295&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 179686295 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15265161 FKZ jtl: American Journal of Bioethics issn: 15265161 maglogo: N pubinfo: dt: Oct2024 vid: 24 iid: 10 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 179686295 179686295 179686295 10.1080/15265161.2024.2388759 179686295 ppf: 76 ppct: 4 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Prudently Evaluating Medical Adaptive Machine Learning Systems. aug: au: Kuersten, Andreas affil: American Law Division, Congressional Research Service, Library of Congress sug: subj: Machine Learning Classification Patient Care Research, Medical Data Analysis, Computer Assisted Machine Learning Ethical Issues Motivation Feedback Debates and Debating Morals Health Personnel Learning Methods Medical Practice Health Care Industry Risk Assessment Privacy and Confidentiality Goals and Objectives Patient Safety pubtype: Academic Journal doctype: commentary Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
|---|