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  • © 2019

Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems

AIME 2019 International Workshops, KR4HC/ProHealth and TEAAM, Poznan, Poland, June 26–29, 2019, Revised Selected Papers

Conference proceedings info: KR4HC 2019, TEAAM 2019.

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Table of contents (13 papers)

  1. Front Matter

    Pages i-xii
  2. KR4HC/ProHealth - Joint Workshop on Knowledge Representation for Health Care and Process-Oriented Information Systems in Health Care

    1. Front Matter

      Pages 1-1
    2. Differential Diagnosis of Bacterial and Viral Meningitis Using Dominance-Based Rough Set Approach

      • Ewelina Gowin, Jerzy Błaszczyński, Roman Słowiński, Jacek Wysocki, Danuta Januszkiewicz-Lewandowska
      Pages 29-38
    3. Deep Learning for Haemodialysis Time Series Classification

      • Giorgio Leonardi, Stefania Montani, Manuel Striani
      Pages 50-64
  3. TEAAM - Workshop on Transparent, Explainable and Affective AI in Medical Systems

    1. Front Matter

      Pages 65-65
    2. Towards Understanding ICU Treatments Using Patient Health Trajectories

      • Alexander Galozy, Sławomir Nowaczyk, Anita Sant’Anna
      Pages 67-81
    3. An Explainable Approach of Inferring Potential Medication Effects from Social Media Data

      • Keyuan Jiang, Tingyu Chen, Liyuan Huang, Ravish Gupta, Ricardo A. Calix, Gordon R. Bernard
      Pages 82-92
    4. Exploring Antimicrobial Resistance Prediction Using Post-hoc Interpretable Methods

      • Bernardo Cánovas-Segura, Antonio Morales, Antonio López Martínez-Carrasco, Manuel Campos, Jose M. Juarez, Lucía López Rodríguez et al.
      Pages 93-107
    5. Local vs. Global Interpretability of Machine Learning Models in Type 2 Diabetes Mellitus Screening

      • Leon Kopitar, Leona Cilar, Primoz Kocbek, Gregor Stiglic
      Pages 108-119
    6. A Computational Framework Towards Medical Image Explanation

      • Xuwen Wang, Yu Zhang, Zhen Guo, Jiao Li
      Pages 120-131
    7. Self-organizing Maps Using Acoustic Features for Prediction of State Change in Bipolar Disorder

      • Olga Kamińska, Katarzyna Kaczmarek-Majer, Karol Opara, Wit Jakuczun, Monika Dominiak, Anna Antosik-Wójcińska et al.
      Pages 148-160
    8. Explainable Machine Learning for Modeling of Early Postoperative Mortality in Lung Cancer

      • Katarzyna Kobylińska, Tomasz Mikołajczyk, Mariusz Adamek, Tadeusz Orłowski, Przemysław Biecek
      Pages 161-174
  4. Back Matter

    Pages 175-175

Other Volumes

  1. Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems

About this book

This book constitutes revised selected papers from the AIME 2019 workshops KR4HC/ProHealth 2019, the Workshop on Knowledge Representation for Health Care and Process-Oriented Information Systems in Health Care, and TEAAM 2019, the Workshop on Transparent, Explainable and Affective AI in Medical Systems.

The volume contains 5 full papers from KR4HC/ProHealth, which were selected out of 13 submissions. For TEAAM 8 papers out of 10 submissions were accepted for publication.

Editors and Affiliations

  • Universitat Jaume I, Castellón, Spain

    Mar Marcos

  • University of Murcia, Murcia, Spain

    Jose M. Juarez

  • Friedrich-Alexander-University of Erlangen-Nuremberg, Erlangen, Germany

    Richard Lenz

  • Jagiellonian University and AGH University of Science and Technology, Kraków, Poland

    Grzegorz J. Nalepa

  • Halmstad University, Halmstad, Sweden

    Slawomir Nowaczyk

  • University of Haifa, Haifa, Israel

    Mor Peleg

  • Poznań University of Technology, Poznan, Poland

    Jerzy Stefanowski

  • University of Maribor, Maribor, Slovenia

    Gregor Stiglic

Bibliographic Information

Buy it now

Buying options

eBook USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access