Custom cover image
Custom cover image

Artificial Intelligence in Health : First International Workshop, AIH 2018, Stockholm, Sweden, July 13-14, 2018, Revised Selected Papers / edited by Fernando Koch, Andrew Koster, David Riaño, Sara Montagna, Michael Schumacher, Annette ten Teije, Christian Guttmann, Manfred Reichert, Isabelle Bichindaritz, Pau Herrero, Richard Lenz, Beatriz López, Cindy Marling, Clare Martin, Stefania Montani, Nirmalie Wiratunga

Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Lecture Notes in Artificial Intelligence ; 11326 | SpringerLink BücherPublisher: Cham : Springer International Publishing, 2019Description: Online-Ressource (XVI, 245 p. 86 illus., 59 illus. in color, online resource)ISBN:
  • 9783030127381
Subject(s): Additional physical formats: 9783030127374 | 9783030127398 | Erscheint auch als: 978-3-030-12737-4 Druck-Ausgabe | Printed edition: 9783030127374 | Printed edition: 9783030127398 DDC classification:
  • 006.3
LOC classification:
  • Q334-342
DOI: DOI: 10.1007/978-3-030-12738-1Online resources: Summary: This book constitutes the refereed post-conference proceedings of the First International Workshop on Artificial Intelligence in Health, AIH 2018, in Stockholm, Sweden, in July 2018. This workshop consolidated the workshops CARE, KRH4C and AI4HC into a single event. The 18 revised full papers included in this volume were carefully selected from the 26 papers accepted for presentation out of 42 initial submissions. The papers present AI technologies with medical applications and are organized in three tracks: agents in healthcare; data science and decision systems in medicine; and knowledge management in healthcarePPN: PPN: 106736790XPackage identifier: Produktsigel: ZDB-2-LNC | ZDB-2-SCS | ZDB-2-SXCS | ZDB-2-SEB
No physical items for this record

Reproduktion. (Springer eBook Collection. Computer Science)

KIT – The Research University in the Helmholtz Association                         Home | Impressum | Datenschutz | Barrierefreiheit | KIT