Insights from explainable interactive machine learning in the age of COVID-19
- COVID-19 HAS AGAIN TIGHTENED ITS GRIP AROUND THE WORLD AND THE HEALTH SYSTEM. THIS ARTICLE GIVES AN INTRODUCTION TO EXPLAINABLE INTERACTIVE MACHINE LEARNING AND PROVIDES INSIGHTS ON HOW THIS METHOD MAY NOT ONLY HELP IN ENGINEERING MORE POWERFUL AI SYSTEMS, BUT ALSO HOW IT MAY HELP TO EASE THE BURDEN OF VIRAL STRAINS ON THE HEALTHCARE SYSTEM.
Author: | Oliver HinzORCiDGND, Nicolas Pfeuffer, Wolfgang Stammer, Patrick Schramowski, Benjamin M. Abdel-KarimORCiDGND, Andreas Bucher, Christian Hügel, Gernot Gerhard Ulrich RohdeORCiDGND, Kristian Kersting |
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URN: | urn:nbn:de:hebis:30:3-576445 |
ISSN: | 1866-1238 |
ISSN: | 2700-2241 |
Parent Title (German): | Efl insights : an elf - the Data Science Institute publication |
Publisher: | E-Finance Lab e.V. |
Place of publication: | Frankfurt am Main |
Document Type: | Article |
Language: | English |
Year of Completion: | 2021 |
Year of first Publication: | 2021 |
Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
Creating Corporation: | E-Finance Lab <Frankfurt, Main> |
Release Date: | 2021/01/22 |
Volume: | 2021 |
Issue: | 1 |
Page Number: | 3 |
First Page: | 6 |
Last Page: | 8 |
HeBIS-PPN: | 477067034 |
Institutes: | Angeschlossene und kooperierende Institutionen / E-Finance Lab e.V. |
Dewey Decimal Classification: | 3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft |
Sammlungen: | Universitätspublikationen |
Licence (German): | ![]() |