MEDICINES MACHINE LEARNING PROBLEM.
In the article, the author discusses the issues on the use of machine learning in medical applications. Also cited are a 2018 survey showing that 84% of U.S. radiology clinics are using or planning to use machine learning software, the book "Deep Medicine: How Artificial Intelligence Can Make Health...
| Published in: | Boston Review Vol. 46; no. 2; pp. 127 - 139 |
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| Format: | Article |
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Boston Review
Spring2021
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=151087990&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 151087990 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 07342306 T0K jtl: Boston Review issn: 07342306 maglogo: N pubinfo: dt: Spring2021 vid: 46 iid: 2 pid: 17044 pub: Boston Review artinfo: ui: 151087990 ppf: 127 ppct: 12 formats: tig: atl: MEDICINES MACHINE LEARNING PROBLEM. aug: au: Tbomas, Racbel su: Machine learning Artificial intelligence in medicine Medical care Artificial intelligence Medical technology sug: subj: Machine learning Artificial intelligence in medicine Medical care Artificial intelligence Medical technology ab: In the article, the author discusses the issues on the use of machine learning in medical applications. Also cited are a 2018 survey showing that 84% of U.S. radiology clinics are using or planning to use machine learning software, the book "Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again" by Eric Topol, and the risks of datafying medicine in the era of artificial intelligence. pubtype: Periodical doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2021 holdings: @attributes: islocal: N |
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