Artificial Intelligence in Medicine

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

  • Annette ten Teije
  • Christian Popow
  • John H. Holmes
  • Lucia Sacchi
Conference proceedings AIME 2017

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

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 10259)

Table of contents

  1. Front Matter
    Pages I-XXV
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  2. Ontologies and Knowledge Representation

    1. Front Matter
      Pages 1-1
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    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
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    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
    6. Accurate Bayesian Prediction of Cardiovascular-Related Mortality Using Ambulatory Blood Pressure Measurements
      James O’Neill, Michael G. Madden, Eamon Dolan
      Pages 86-91

  4. Temporal Methods

    1. Front Matter
      Pages 93-93
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    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
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About these proceedings

Introduction

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. 

Keywords

artificial intelligence machine learning natural language processing ontologies Bayesian networks knowledge representation and reasoning data mining text mining machine learning algorithms information extraction clinical decision support sytems computer-aided diagnosis probabilistic reasoning modeling methodologies biomedical informatics statistics support vector machines

Editors and affiliations

  1. 1.Vrije Universiteit AmsterdamAmsterdamThe Netherlands
  2. 2.Medical University of ViennaViennaAustria
  3. 3.University of PennsylvaniaPhiladelphiaUSA
  4. 4.University of PaviaPaviaItaly

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-59758-4
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-59757-7
  • Online ISBN 978-3-319-59758-4
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site