Skip to main content
SpringerLink
Log in

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
  • © 2019

Overview

Editors:
  1. Mar Marcos

    1. Universitat Jaume I, Castellón, Spain

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Jose M. Juarez

    1. University of Murcia, Murcia, Spain

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  3. Richard Lenz

    1. Friedrich-Alexander-University of Erlangen-Nuremberg, Erlangen, Germany

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  4. Grzegorz J. Nalepa

    1. Jagiellonian University and AGH University of Science and Technology, Kraków, Poland

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  5. Slawomir Nowaczyk

    1. Halmstad University, Halmstad, Sweden

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  6. Mor Peleg

    1. University of Haifa, Haifa, Israel

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  7. Jerzy Stefanowski

    1. Poznań University of Technology, Poznan, Poland

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  8. Gregor Stiglic

    1. University of Maribor, Maribor, Slovenia

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11979)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
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

Licence this eBook for your library

Institutional subscriptions

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.

Similar content being viewed by others

Keywords

Table of contents (13 papers)

  1. Front Matter

    Pages i-xii
    Download chapter PDF

  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
      Download chapter PDF

    2. A Practical Exercise on Re-engineering Clinical Guideline Models Using Different Representation Languages

      • Mar Marcos, Cristina Campos, Begoña Martínez-Salvador
      Pages 3-16

    3. A Method for Goal-Oriented Guideline Modeling in PROforma and Its Preliminary Evaluation

      • Mor Peleg, Alexandra Kogan, Samson W. Tu
      Pages 17-28

    4. 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

    5. Modelling ICU Patients to Improve Care Requirements and Outcome Prediction of Acute Respiratory Distress Syndrome: A Supervised Learning Approach

      • Mohammed Sayed, David Riaño
      Pages 39-49

    6. 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
      Download chapter PDF

    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. A Computational Framework for Interpretable Anomaly Detection and Classification of Multivariate Time Series with Application to Human Gait Data Analysis

      • Erica Ramirez, Markus Wimmer, Martin Atzmueller
      Pages 132-147

    8. 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

    9. 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
    Download chapter PDF
Back to top

Other volumes

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

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

Publish with us

Policies and ethics

Back to top

Search

Navigation