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Artificial Intelligence in Medicine

17th Conference on Artificial Intelligence in Medicine, AIME 2019, Poznan, Poland, June 26–29, 2019, Proceedings

  • Conference proceedings
  • © 2019

Overview

Editors:
  1. David Riaño

    1. Universitat Rovira i Virgili, Tarragona, Spain

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  2. Szymon Wilk

    1. Poznan University of Technology, Poznan, Poland

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    You can also search for this editor in PubMed   Google Scholar

  3. Annette ten Teije

    1. VU Amsterdam, Amsterdam, The Netherlands

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11526)

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

Included in the following conference series:

Conference proceedings info: AIME 2019.

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Table of contents (53 papers)

  1. Front Matter

    Pages i-xviii
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  3. Deep Learning

    1. Front Matter

      Pages 11-11
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    2. Recent Context-Aware LSTM for Clinical Event Time-Series Prediction

      • Jeong Min Lee, Milos Hauskrecht
      Pages 13-23

    3. Deep Learning Approach for Pathogen Detection Through Shotgun Metagenomics Sequence Classification

      • Ying-Feng Hsu, Makiko Ito, Takumi Maruyama, Morito Matsuoka, Nicolas Jung, Yuki Matsumoto et al.
      Pages 24-30

    4. Fully Interactive Lungs Auscultation with AI Enabled Digital Stethoscope

      • Tomasz Grzywalski, Riccardo Belluzzo, Mateusz Piecuch, Marcin Szajek, Anna Bręborowicz, Anna Pastusiak et al.
      Pages 31-35

    5. An Automated Fall Detection System Using Recurrent Neural Networks

      • Francisco Luna-Perejon, Javier Civit-Masot, Isabel Amaya-Rodriguez, Lourdes Duran-Lopez, Juan Pedro Dominguez-Morales, Anton Civit-Balcells et al.
      Pages 36-41

    6. A Semi-supervised Learning Approach for Pan-Cancer Somatic Genomic Variant Classification

      • Giovanna Nicora, Simone Marini, Ivan Limongelli, Ettore Rizzo, Stefano Montoli, Francesca Floriana Tricomi et al.
      Pages 42-46

    7. ChronoNet: A Deep Recurrent Neural Network for Abnormal EEG Identification

      • Subhrajit Roy, Isabell Kiral-Kornek, Stefan Harrer
      Pages 47-56

    8. Convolutional Recurrent Neural Network for Bubble Detection in a Portable Continuous Bladder Irrigation Monitor

      • Xiaoying Tan, Gerd Reis, Didier Stricker
      Pages 57-66

    9. Mammogram Classification with Ordered Loss

      • Rami Ben-Ari, Yoel Shoshan, Tal Tlusty
      Pages 67-76

  4. Simulation

    1. Front Matter

      Pages 77-77
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    2. Agent-Based Models and Spatial Enablement: A Simulation Tool to Improve Health and Wellbeing in Big Cities

      • Daniele Pala, John Holmes, José Pagàn, Enea Parimbelli, Marica Teresa Rocca, Vittorio Casella et al.
      Pages 79-83

    3. Towards Health 4.0: e-Hospital Proposal Based Industry 4.0 and Artificial Intelligence Concepts

      • Camilo Cáceres, Joao Mauricio Rosário, Dario Amaya
      Pages 84-89

  5. Knowledge Representation

    1. Front Matter

      Pages 91-91
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    2. MitPlan: A Planning Approach to Mitigating Concurrently Applied Clinical Practice Guidelines

      • Martin Michalowski, Szymon Wilk, Wojtek Michalowski, Marc Carrier
      Pages 93-103

    3. Automatic Alignment of Surgical Videos Using Kinematic Data

      • Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, François Petitjean, Lhassane Idoumghar, Pierre-Alain Muller
      Pages 104-113

    4. A Rule-Based Expert System for Automatic Implementation of Somatic Variant Clinical Interpretation Guidelines

      • Giovanna Nicora, Ivan Limongelli, Riccardo Cova, Matteo Giovanni Della Porta, Luca Malcovati, Mario Cazzola et al.
      Pages 114-119
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  1. Artificial Intelligence in Medicine

Keywords

About this book

This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019.
The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.

Editors and Affiliations

  • Universitat Rovira i Virgili, Tarragona, Spain

    David Riaño

  • Poznan University of Technology, Poznan, Poland

    Szymon Wilk

  • VU Amsterdam, Amsterdam, The Netherlands

    Annette ten Teije

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