Explainable Artificial Intelligence and Process Mining Applications for Healthcare | Third International Workshop, XAI-Healthcare 2023, and First International Workshop, PM4H 2023, Portoroz, Slovenia, June 15, 2023, Proceedings

Jose M. Juarez (u. a.)

ISBN 10: 3031543025 / ISBN 13: 9783031543029

Published by Springer, 2024

About this Item

Explainable Artificial Intelligence and Process Mining Applications for Healthcare | Third International Workshop, XAI-Healthcare 2023, and First International Workshop, PM4H 2023, Portoroz, Slovenia, June 15, 2023, Proceedings | Jose M. Juarez (u. a.) | Taschenbuch | xii | Englisch | 2024 | Springer | EAN 9783031543029 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

Seller Inventory # 128321678

Bibliographic Details

• Title: Explainable Artificial Intelligence and Process Mining Applications for Healthcare | Third International Workshop, XAI-Healthcare 2023, and First International Workshop, PM4H 2023, Portoroz, Slovenia, June 15, 2023, Proceedings
• Publisher: Springer
• Publication Date: 2024
• Language: English
• ISBN 10: 3031543025
• ISBN 13: 9783031543029
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 9D millimeters 235 millimeters width by 155 millimeters height by 9 millimeters depth
• Weight: 230 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

This book constitutes the proceedings of the Third International Workshop on Explainable Artificial Intelligence in Healthcare, XAI-Healthcare 2023, and the First International Workshop on Process Mining Applications for Healthcare, PM4H 2023, which took place in conjunction with AIME 2023 in Portoroz, Slovenia, on June 15, 2023.

The 7 full papers included from XAI-Healthcare were carefully reviewed and selected from 11 submissions. They focus on all aspects of eXplainable Artificial Intelligence (XAI) in the medical and healthcare field. For PM4H 5 papers have been accepted from 17 submissions. They deal with data-driven process analysis techniques in healthcare.