Ethical considerations in artificial intelligence
• As in the case of most disruptive technologies, assessment of and consensus on the possible ethical pitfalls lag. • selection bias in AI datasets can result in inaccurate results in under-represented patient groups. • AI models with imaging data acquired from one setting may poorly generalize to o...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Safdar, Nabile M. [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2020 |
|---|
| Schlagwörter: |
|---|
| Übergeordnetes Werk: |
Enthalten in: Spray with plant growth regulators at full bloom may improve quality for storage of 'Superior Seedless' table grapes by modifying the vascular system of the bunch - Guzmán, Yanina ELSEVIER, 2021, EJR, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:122 ; year:2020 ; pages:0 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.ejrad.2019.108768 |
|---|
| Katalog-ID: |
ELV048958255 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | ELV048958255 | ||
| 003 | DE-627 | ||
| 005 | 20230624151219.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 200108s2020 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.ejrad.2019.108768 |2 doi | |
| 028 | 5 | 2 | |a /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000859.pica |
| 035 | |a (DE-627)ELV048958255 | ||
| 035 | |a (ELSEVIER)S0720-048X(19)30418-8 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 570 |a 630 |q VZ |
| 084 | |a BIODIV |q DE-30 |2 fid | ||
| 084 | |a 58.34 |2 bkl | ||
| 084 | |a 48.59 |2 bkl | ||
| 100 | 1 | |a Safdar, Nabile M. |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Ethical considerations in artificial intelligence |
| 264 | 1 | |c 2020 | |
| 336 | |a nicht spezifiziert |b zzz |2 rdacontent | ||
| 337 | |a nicht spezifiziert |b z |2 rdamedia | ||
| 338 | |a nicht spezifiziert |b zu |2 rdacarrier | ||
| 520 | |a • As in the case of most disruptive technologies, assessment of and consensus on the possible ethical pitfalls lag. • selection bias in AI datasets can result in inaccurate results in under-represented patient groups. • AI models with imaging data acquired from one setting may poorly generalize to other practice settings. • Patient image data ownership regulations vary by country and domain. • De-identification of image data used in AI algorithms may inadvertently reveal protected health information. | ||
| 650 | 7 | |a Ethics |2 Elsevier | |
| 650 | 7 | |a Machine learning |2 Elsevier | |
| 650 | 7 | |a Radiology |2 Elsevier | |
| 650 | 7 | |a Artificial intelligence |2 Elsevier | |
| 700 | 1 | |a Banja, John D. |4 oth | |
| 700 | 1 | |a Meltzer, Carolyn C. |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier Science |a Guzmán, Yanina ELSEVIER |t Spray with plant growth regulators at full bloom may improve quality for storage of 'Superior Seedless' table grapes by modifying the vascular system of the bunch |d 2021 |d EJR |g Amsterdam [u.a.] |w (DE-627)ELV005739942 |
| 773 | 1 | 8 | |g volume:122 |g year:2020 |g pages:0 |
| 856 | 4 | 0 | |u https://doi.org/10.1016/j.ejrad.2019.108768 |3 Volltext |
| 912 | |a GBV_USEFLAG_U | ||
| 912 | |a GBV_ELV | ||
| 912 | |a SYSFLAG_U | ||
| 912 | |a FID-BIODIV | ||
| 912 | |a SSG-OLC-PHA | ||
| 936 | b | k | |a 58.34 |j Lebensmitteltechnologie |q VZ |
| 936 | b | k | |a 48.59 |j Pflanzenproduktion: Sonstiges |q VZ |
| 951 | |a AR | ||
| 952 | |d 122 |j 2020 |h 0 | ||
| author_variant |
n m s nm nms |
|---|---|
| matchkey_str |
safdarnabilembanjajohndmeltzercarolync:2020----:tiacnieainiatfca |
| hierarchy_sort_str |
2020 |
| bklnumber |
58.34 48.59 |
| publishDate |
2020 |
| allfields |
10.1016/j.ejrad.2019.108768 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000859.pica (DE-627)ELV048958255 (ELSEVIER)S0720-048X(19)30418-8 DE-627 ger DE-627 rakwb eng 570 630 VZ BIODIV DE-30 fid 58.34 bkl 48.59 bkl Safdar, Nabile M. verfasserin aut Ethical considerations in artificial intelligence 2020 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • As in the case of most disruptive technologies, assessment of and consensus on the possible ethical pitfalls lag. • selection bias in AI datasets can result in inaccurate results in under-represented patient groups. • AI models with imaging data acquired from one setting may poorly generalize to other practice settings. • Patient image data ownership regulations vary by country and domain. • De-identification of image data used in AI algorithms may inadvertently reveal protected health information. Ethics Elsevier Machine learning Elsevier Radiology Elsevier Artificial intelligence Elsevier Banja, John D. oth Meltzer, Carolyn C. oth Enthalten in Elsevier Science Guzmán, Yanina ELSEVIER Spray with plant growth regulators at full bloom may improve quality for storage of 'Superior Seedless' table grapes by modifying the vascular system of the bunch 2021 EJR Amsterdam [u.a.] (DE-627)ELV005739942 volume:122 year:2020 pages:0 https://doi.org/10.1016/j.ejrad.2019.108768 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 58.34 Lebensmitteltechnologie VZ 48.59 Pflanzenproduktion: Sonstiges VZ AR 122 2020 0 |
| spelling |
10.1016/j.ejrad.2019.108768 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000859.pica (DE-627)ELV048958255 (ELSEVIER)S0720-048X(19)30418-8 DE-627 ger DE-627 rakwb eng 570 630 VZ BIODIV DE-30 fid 58.34 bkl 48.59 bkl Safdar, Nabile M. verfasserin aut Ethical considerations in artificial intelligence 2020 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • As in the case of most disruptive technologies, assessment of and consensus on the possible ethical pitfalls lag. • selection bias in AI datasets can result in inaccurate results in under-represented patient groups. • AI models with imaging data acquired from one setting may poorly generalize to other practice settings. • Patient image data ownership regulations vary by country and domain. • De-identification of image data used in AI algorithms may inadvertently reveal protected health information. Ethics Elsevier Machine learning Elsevier Radiology Elsevier Artificial intelligence Elsevier Banja, John D. oth Meltzer, Carolyn C. oth Enthalten in Elsevier Science Guzmán, Yanina ELSEVIER Spray with plant growth regulators at full bloom may improve quality for storage of 'Superior Seedless' table grapes by modifying the vascular system of the bunch 2021 EJR Amsterdam [u.a.] (DE-627)ELV005739942 volume:122 year:2020 pages:0 https://doi.org/10.1016/j.ejrad.2019.108768 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 58.34 Lebensmitteltechnologie VZ 48.59 Pflanzenproduktion: Sonstiges VZ AR 122 2020 0 |
| allfields_unstemmed |
10.1016/j.ejrad.2019.108768 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000859.pica (DE-627)ELV048958255 (ELSEVIER)S0720-048X(19)30418-8 DE-627 ger DE-627 rakwb eng 570 630 VZ BIODIV DE-30 fid 58.34 bkl 48.59 bkl Safdar, Nabile M. verfasserin aut Ethical considerations in artificial intelligence 2020 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • As in the case of most disruptive technologies, assessment of and consensus on the possible ethical pitfalls lag. • selection bias in AI datasets can result in inaccurate results in under-represented patient groups. • AI models with imaging data acquired from one setting may poorly generalize to other practice settings. • Patient image data ownership regulations vary by country and domain. • De-identification of image data used in AI algorithms may inadvertently reveal protected health information. Ethics Elsevier Machine learning Elsevier Radiology Elsevier Artificial intelligence Elsevier Banja, John D. oth Meltzer, Carolyn C. oth Enthalten in Elsevier Science Guzmán, Yanina ELSEVIER Spray with plant growth regulators at full bloom may improve quality for storage of 'Superior Seedless' table grapes by modifying the vascular system of the bunch 2021 EJR Amsterdam [u.a.] (DE-627)ELV005739942 volume:122 year:2020 pages:0 https://doi.org/10.1016/j.ejrad.2019.108768 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 58.34 Lebensmitteltechnologie VZ 48.59 Pflanzenproduktion: Sonstiges VZ AR 122 2020 0 |
| allfieldsGer |
10.1016/j.ejrad.2019.108768 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000859.pica (DE-627)ELV048958255 (ELSEVIER)S0720-048X(19)30418-8 DE-627 ger DE-627 rakwb eng 570 630 VZ BIODIV DE-30 fid 58.34 bkl 48.59 bkl Safdar, Nabile M. verfasserin aut Ethical considerations in artificial intelligence 2020 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • As in the case of most disruptive technologies, assessment of and consensus on the possible ethical pitfalls lag. • selection bias in AI datasets can result in inaccurate results in under-represented patient groups. • AI models with imaging data acquired from one setting may poorly generalize to other practice settings. • Patient image data ownership regulations vary by country and domain. • De-identification of image data used in AI algorithms may inadvertently reveal protected health information. Ethics Elsevier Machine learning Elsevier Radiology Elsevier Artificial intelligence Elsevier Banja, John D. oth Meltzer, Carolyn C. oth Enthalten in Elsevier Science Guzmán, Yanina ELSEVIER Spray with plant growth regulators at full bloom may improve quality for storage of 'Superior Seedless' table grapes by modifying the vascular system of the bunch 2021 EJR Amsterdam [u.a.] (DE-627)ELV005739942 volume:122 year:2020 pages:0 https://doi.org/10.1016/j.ejrad.2019.108768 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 58.34 Lebensmitteltechnologie VZ 48.59 Pflanzenproduktion: Sonstiges VZ AR 122 2020 0 |
| allfieldsSound |
10.1016/j.ejrad.2019.108768 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000859.pica (DE-627)ELV048958255 (ELSEVIER)S0720-048X(19)30418-8 DE-627 ger DE-627 rakwb eng 570 630 VZ BIODIV DE-30 fid 58.34 bkl 48.59 bkl Safdar, Nabile M. verfasserin aut Ethical considerations in artificial intelligence 2020 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • As in the case of most disruptive technologies, assessment of and consensus on the possible ethical pitfalls lag. • selection bias in AI datasets can result in inaccurate results in under-represented patient groups. • AI models with imaging data acquired from one setting may poorly generalize to other practice settings. • Patient image data ownership regulations vary by country and domain. • De-identification of image data used in AI algorithms may inadvertently reveal protected health information. Ethics Elsevier Machine learning Elsevier Radiology Elsevier Artificial intelligence Elsevier Banja, John D. oth Meltzer, Carolyn C. oth Enthalten in Elsevier Science Guzmán, Yanina ELSEVIER Spray with plant growth regulators at full bloom may improve quality for storage of 'Superior Seedless' table grapes by modifying the vascular system of the bunch 2021 EJR Amsterdam [u.a.] (DE-627)ELV005739942 volume:122 year:2020 pages:0 https://doi.org/10.1016/j.ejrad.2019.108768 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 58.34 Lebensmitteltechnologie VZ 48.59 Pflanzenproduktion: Sonstiges VZ AR 122 2020 0 |
| language |
English |
| source |
Enthalten in Spray with plant growth regulators at full bloom may improve quality for storage of 'Superior Seedless' table grapes by modifying the vascular system of the bunch Amsterdam [u.a.] volume:122 year:2020 pages:0 |
| sourceStr |
Enthalten in Spray with plant growth regulators at full bloom may improve quality for storage of 'Superior Seedless' table grapes by modifying the vascular system of the bunch Amsterdam [u.a.] volume:122 year:2020 pages:0 |
| format_phy_str_mv |
Article |
| bklname |
Lebensmitteltechnologie Pflanzenproduktion: Sonstiges |
| institution |
findex.gbv.de |
| topic_facet |
Ethics Machine learning Radiology Artificial intelligence |
| dewey-raw |
570 |
| isfreeaccess_bool |
false |
| container_title |
Spray with plant growth regulators at full bloom may improve quality for storage of 'Superior Seedless' table grapes by modifying the vascular system of the bunch |
| authorswithroles_txt_mv |
Safdar, Nabile M. @@aut@@ Banja, John D. @@oth@@ Meltzer, Carolyn C. @@oth@@ |
| publishDateDaySort_date |
2020-01-01T00:00:00Z |
| hierarchy_top_id |
ELV005739942 |
| dewey-sort |
3570 |
| id |
ELV048958255 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV048958255</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230624151219.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">200108s2020 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.ejrad.2019.108768</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">/cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000859.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV048958255</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0720-048X(19)30418-8</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">570</subfield><subfield code="a">630</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">BIODIV</subfield><subfield code="q">DE-30</subfield><subfield code="2">fid</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">58.34</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">48.59</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Safdar, Nabile M.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Ethical considerations in artificial intelligence</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">• As in the case of most disruptive technologies, assessment of and consensus on the possible ethical pitfalls lag. • selection bias in AI datasets can result in inaccurate results in under-represented patient groups. • AI models with imaging data acquired from one setting may poorly generalize to other practice settings. • Patient image data ownership regulations vary by country and domain. • De-identification of image data used in AI algorithms may inadvertently reveal protected health information.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Ethics</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Machine learning</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Radiology</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Artificial intelligence</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Banja, John D.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Meltzer, Carolyn C.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier Science</subfield><subfield code="a">Guzmán, Yanina ELSEVIER</subfield><subfield code="t">Spray with plant growth regulators at full bloom may improve quality for storage of 'Superior Seedless' table grapes by modifying the vascular system of the bunch</subfield><subfield code="d">2021</subfield><subfield code="d">EJR</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV005739942</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:122</subfield><subfield code="g">year:2020</subfield><subfield code="g">pages:0</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.ejrad.2019.108768</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">FID-BIODIV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">58.34</subfield><subfield code="j">Lebensmitteltechnologie</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">48.59</subfield><subfield code="j">Pflanzenproduktion: Sonstiges</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">122</subfield><subfield code="j">2020</subfield><subfield code="h">0</subfield></datafield></record></collection>
|
| author |
Safdar, Nabile M. |
| spellingShingle |
Safdar, Nabile M. ddc 570 fid BIODIV bkl 58.34 bkl 48.59 Elsevier Ethics Elsevier Machine learning Elsevier Radiology Elsevier Artificial intelligence Ethical considerations in artificial intelligence |
| authorStr |
Safdar, Nabile M. |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)ELV005739942 |
| format |
electronic Article |
| dewey-ones |
570 - Life sciences; biology 630 - Agriculture & related technologies |
| delete_txt_mv |
keep |
| author_role |
aut |
| collection |
elsevier |
| remote_str |
true |
| illustrated |
Not Illustrated |
| topic_title |
570 630 VZ BIODIV DE-30 fid 58.34 bkl 48.59 bkl Ethical considerations in artificial intelligence Ethics Elsevier Machine learning Elsevier Radiology Elsevier Artificial intelligence Elsevier |
| topic |
ddc 570 fid BIODIV bkl 58.34 bkl 48.59 Elsevier Ethics Elsevier Machine learning Elsevier Radiology Elsevier Artificial intelligence |
| topic_unstemmed |
ddc 570 fid BIODIV bkl 58.34 bkl 48.59 Elsevier Ethics Elsevier Machine learning Elsevier Radiology Elsevier Artificial intelligence |
| topic_browse |
ddc 570 fid BIODIV bkl 58.34 bkl 48.59 Elsevier Ethics Elsevier Machine learning Elsevier Radiology Elsevier Artificial intelligence |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
zu |
| author2_variant |
j d b jd jdb c c m cc ccm |
| hierarchy_parent_title |
Spray with plant growth regulators at full bloom may improve quality for storage of 'Superior Seedless' table grapes by modifying the vascular system of the bunch |
| hierarchy_parent_id |
ELV005739942 |
| dewey-tens |
570 - Life sciences; biology 630 - Agriculture |
| hierarchy_top_title |
Spray with plant growth regulators at full bloom may improve quality for storage of 'Superior Seedless' table grapes by modifying the vascular system of the bunch |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)ELV005739942 |
| title |
Ethical considerations in artificial intelligence |
| ctrlnum |
(DE-627)ELV048958255 (ELSEVIER)S0720-048X(19)30418-8 |
| title_full |
Ethical considerations in artificial intelligence |
| author_sort |
Safdar, Nabile M. |
| journal |
Spray with plant growth regulators at full bloom may improve quality for storage of 'Superior Seedless' table grapes by modifying the vascular system of the bunch |
| journalStr |
Spray with plant growth regulators at full bloom may improve quality for storage of 'Superior Seedless' table grapes by modifying the vascular system of the bunch |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
500 - Science 600 - Technology |
| recordtype |
marc |
| publishDateSort |
2020 |
| contenttype_str_mv |
zzz |
| container_start_page |
0 |
| author_browse |
Safdar, Nabile M. |
| container_volume |
122 |
| class |
570 630 VZ BIODIV DE-30 fid 58.34 bkl 48.59 bkl |
| format_se |
Elektronische Aufsätze |
| author-letter |
Safdar, Nabile M. |
| doi_str_mv |
10.1016/j.ejrad.2019.108768 |
| dewey-full |
570 630 |
| title_sort |
ethical considerations in artificial intelligence |
| title_auth |
Ethical considerations in artificial intelligence |
| abstract |
• As in the case of most disruptive technologies, assessment of and consensus on the possible ethical pitfalls lag. • selection bias in AI datasets can result in inaccurate results in under-represented patient groups. • AI models with imaging data acquired from one setting may poorly generalize to other practice settings. • Patient image data ownership regulations vary by country and domain. • De-identification of image data used in AI algorithms may inadvertently reveal protected health information. |
| abstractGer |
• As in the case of most disruptive technologies, assessment of and consensus on the possible ethical pitfalls lag. • selection bias in AI datasets can result in inaccurate results in under-represented patient groups. • AI models with imaging data acquired from one setting may poorly generalize to other practice settings. • Patient image data ownership regulations vary by country and domain. • De-identification of image data used in AI algorithms may inadvertently reveal protected health information. |
| abstract_unstemmed |
• As in the case of most disruptive technologies, assessment of and consensus on the possible ethical pitfalls lag. • selection bias in AI datasets can result in inaccurate results in under-represented patient groups. • AI models with imaging data acquired from one setting may poorly generalize to other practice settings. • Patient image data ownership regulations vary by country and domain. • De-identification of image data used in AI algorithms may inadvertently reveal protected health information. |
| collection_details |
GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA |
| title_short |
Ethical considerations in artificial intelligence |
| url |
https://doi.org/10.1016/j.ejrad.2019.108768 |
| remote_bool |
true |
| author2 |
Banja, John D. Meltzer, Carolyn C. |
| author2Str |
Banja, John D. Meltzer, Carolyn C. |
| ppnlink |
ELV005739942 |
| mediatype_str_mv |
z |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| author2_role |
oth oth |
| doi_str |
10.1016/j.ejrad.2019.108768 |
| up_date |
2024-07-06T20:14:36.269Z |
| _version_ |
1803862017331691520 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV048958255</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230624151219.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">200108s2020 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.ejrad.2019.108768</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">/cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000859.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV048958255</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0720-048X(19)30418-8</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">570</subfield><subfield code="a">630</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">BIODIV</subfield><subfield code="q">DE-30</subfield><subfield code="2">fid</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">58.34</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">48.59</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Safdar, Nabile M.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Ethical considerations in artificial intelligence</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">• As in the case of most disruptive technologies, assessment of and consensus on the possible ethical pitfalls lag. • selection bias in AI datasets can result in inaccurate results in under-represented patient groups. • AI models with imaging data acquired from one setting may poorly generalize to other practice settings. • Patient image data ownership regulations vary by country and domain. • De-identification of image data used in AI algorithms may inadvertently reveal protected health information.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Ethics</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Machine learning</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Radiology</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Artificial intelligence</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Banja, John D.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Meltzer, Carolyn C.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier Science</subfield><subfield code="a">Guzmán, Yanina ELSEVIER</subfield><subfield code="t">Spray with plant growth regulators at full bloom may improve quality for storage of 'Superior Seedless' table grapes by modifying the vascular system of the bunch</subfield><subfield code="d">2021</subfield><subfield code="d">EJR</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV005739942</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:122</subfield><subfield code="g">year:2020</subfield><subfield code="g">pages:0</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.ejrad.2019.108768</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">FID-BIODIV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">58.34</subfield><subfield code="j">Lebensmitteltechnologie</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">48.59</subfield><subfield code="j">Pflanzenproduktion: Sonstiges</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">122</subfield><subfield code="j">2020</subfield><subfield code="h">0</subfield></datafield></record></collection>
|
| score |
7.4031916 |