TY  - JOUR
A1  - Hinz, Oliver
A1  - Pfeuffer, Nicolas
A1  - Stammer, Wolfgang
A1  - Schramowski, Patrick
A1  - Abdel-Karim, Benjamin M.
A1  - Bucher, Andreas
A1  - Hügel, Christian
A1  - Rohde, Gernot Gerhard Ulrich
A1  - Kersting, Kristian
T1  - Insights from explainable interactive machine learning in the age of COVID-19
T2  - Efl insights : an elf - the Data Science Institute publication
N2  - 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.
Y1  - 2021
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/57644
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-576445
SN  - 1866-1238
SN  - 2700-2241
VL  - 2021
IS  - 1
SP  - 6
EP  - 8
PB  - E-Finance Lab e.V.
CY  - Frankfurt am Main
ER  -