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  • © 2017

Artificial Intelligence in Medicine

16th Conference on Artificial Intelligence in Medicine, AIME 2017, Vienna, Austria, June 21-24, 2017, Proceedings

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10259)

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

Conference series link(s): AIME: International Conference on Artificial Intelligence in Medicine

Conference proceedings info: AIME 2017.

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Table of contents (44 papers)

  1. Front Matter

    Pages I-XXV
  2. Ontologies and Knowledge Representation

    1. Front Matter

      Pages 1-1
    2. Studying the Reuse of Content in Biomedical Ontologies: An Axiom-Based Approach

      • Manuel Quesada-Martínez, Jesualdo Tomás Fernández-Breis
      Pages 3-13
    3. Ontological Representation of Laboratory Test Observables: Challenges and Perspectives in the SNOMED CT Observable Entity Model Adoption

      • Mélissa Mary, Lina F. Soualmia, Xavier Gansel, Stéfan Darmoni, Daniel Karlsson, Stefan Schulz
      Pages 14-23
    4. CAREDAS: Context and Activity Recognition Enabling Detection of Anomalous Situation

      • Hela Sfar, Nathan Ramoly, Amel Bouzeghoub, Beatrice Finance
      Pages 24-36
    5. Using Constraint Logic Programming for the Verification of Customized Decision Models for Clinical Guidelines

      • Szymon Wilk, Adi Fux, Martin Michalowski, Mor Peleg, Pnina Soffer
      Pages 37-47
    6. Constructing Disease-Centric Knowledge Graphs: A Case Study for Depression (short Version)

      • Zhisheng Huang, Jie Yang, Frank van Harmelen, Qing Hu
      Pages 48-52
  3. Bayesian Methods

    1. Front Matter

      Pages 53-53
    2. Implementing Guidelines for Causality Assessment of Adverse Drug Reaction Reports: A Bayesian Network Approach

      • Pedro Pereira Rodrigues, Daniela Ferreira-Santos, Ana Silva, Jorge Polónia, Inês Ribeiro-Vaz
      Pages 55-64
    3. Bayesian Gaussian Process Classification from Event-Related Brain Potentials in Alzheimer’s Disease

      • Wolfgang Fruehwirt, Pengfei Zhang, Matthias Gerstgrasser, Dieter Grossegger, Reinhold Schmidt, Thomas Benke et al.
      Pages 65-75
    4. Data Fusion Approach for Learning Transcriptional Bayesian Networks

      • Elisabetta Sauta, Andrea Demartini, Francesca Vitali, Alberto Riva, Riccardo Bellazzi
      Pages 76-80
    5. A Prognostic Model of Glioblastoma Multiforme Using Survival Bayesian Networks

      • Simon Rabinowicz, Arjen Hommersom, Raphaela Butz, Matt Williams
      Pages 81-85
  4. Temporal Methods

    1. Front Matter

      Pages 93-93
    2. Modelling Time-Series of Glucose Measurements from Diabetes Patients Using Predictive Clustering Trees

      • Mate Beštek, Dragi Kocev, Sašo Džeroski, Andrej Brodnik, Rade Iljaž
      Pages 95-104
    3. Estimation of Sleep Quality by Using Microstructure Profiles

      • Zuzana Rošt’áková, Georg Dorffner, Önder Aydemir, Roman Rosipal
      Pages 105-115
    4. Combining Multitask Learning and Short Time Series Analysis in Parkinson’s Disease Patients Stratification

      • Anita Valmarska, Dragana Miljkovic, Spiros Konitsiotis, Dimitris Gatsios, Nada Lavrač, Marko Robnik-Šikonja
      Pages 116-125
    5. Change-Point Detection Method for Clinical Decision Support System Rule Monitoring

      • Siqi Liu, Adam Wright, Milos Hauskrecht
      Pages 126-135
    6. Discovering Discriminative and Interpretable Patterns for Surgical Motion Analysis

      • Germain Forestier, François Petitjean, Pavel Senin, Fabien Despinoy, Pierre Jannin
      Pages 136-145
  5. Natural Language Processing

    1. Front Matter

      Pages 147-147

Other Volumes

  1. Artificial Intelligence in Medicine

About this book

This book constitutes the refereed proceedings of the 16th Conference on Artificial Intelligence in Medicine, AIME 2017, held in Vienna, Austria, in June 2017.
The 21 revised full and 23 short papers presented were carefully reviewed and selected from 113 submissions. The papers are organized in the following topical sections: ontologies and knowledge representation; Bayesian methods; temporal methods; natural language processing; health care processes; and machine learning, and a section with demo papers. 


Editors and Affiliations

  • Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Annette ten Teije

  • Medical University of Vienna, Vienna, Austria

    Christian Popow

  • University of Pennsylvania, Philadelphia, USA

    John H. Holmes

  • University of Pavia, Pavia, Italy

    Lucia Sacchi

Bibliographic Information

Buy it now

Buying options

eBook USD 54.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 69.99
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