Explainability based on feature importance for better comprehension of machine learning in healthcare
Das PP, Wiese L, ELISE Study Group
Research article in edited proceedings (conference) | Peer reviewedDetails about the publication
Editors: Abelló A, Vassiliadis P, Romero O, Wrembel R, Bugiotti F, Gamper J, Vargas Solar G, Zumpano E
Book title: New Trends in Database and Information Systems
Page range: 324-335
Publisher: Springer
Place of publication: Cham
Status: Published
Release year: 2023
Conference: EXEC-MAN (EXplainable hEalthCare data Management and ANalytics), Barcelona, Spain
Link to the full text: https://link.springer.com/chapter/10.1007/978-3-031-42941-5_28
Keywords: Explainability; AI
Authors from the University of Münster
| Böhnke, Julia | |
| Karch, André | |
| Rübsamen, Nicole |
Projects the publication originates from
Ein Lernendes und Interoperables, Smartes Expertensystem für die pädiatrische Intensivmedizin (ELISE) Duration: 01/10/2020 - 30/09/2023 Funded by: Federal Ministry of Health Type of project: Participation in federally funded joint project |