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Artificial Intelligence in Medicine

19th International Conference on Artificial Intelligence in Medicine, AIME 2021, Virtual Event, June 15–18, 2021, Proceedings

  • Conference proceedings
  • © 2021

Overview

Editors:
  1. Allan Tucker

    1. Brunel University London, Uxbridge, UK

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  2. Pedro Henriques Abreu

    1. University of Coimbra, Coimbra, Portugal

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  3. Jaime Cardoso

    1. University of Porto, Porto, Portugal

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  4. Pedro Pereira Rodrigues

    1. University of Porto, Porto, Portugal

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  5. David Riaño

    1. Universitat Rovira i Virgili, Tarragona, Spain

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12721)

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

Included in the following conference series:

Conference proceedings info: AIME 2021.

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Table of contents (59 papers)

  1. Front Matter

    Pages i-xx
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  2. Invited Talk

    1. Front Matter

      Pages 1-1
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    2. The Myth of Complete AI-Fairness

      • Virginia Dignum
      Pages 3-8

  3. Image Analysis

    1. Front Matter

      Pages 9-9
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    2. A Petri Dish for Histopathology Image Analysis

      • Jerry Wei, Arief Suriawinata, Bing Ren, Xiaoying Liu, Mikhail Lisovsky, Louis Vaickus et al.
      Pages 11-24

    3. fMRI Multiple Missing Values Imputation Regularized by a Recurrent Denoiser

      • David Calhas, Rui Henriques
      Pages 25-35

    4. Bayesian Deep Active Learning for Medical Image Analysis

      • Biraja Ghoshal, Stephen Swift, Allan Tucker
      Pages 36-42

    5. A Topological Data Analysis Mapper of the Ovarian Folliculogenesis Based on MALDI Mass Spectrometry Imaging Proteomics

      • Giulia Campi, Giovanna Nicora, Giulia Fiorentino, Andrew Smith, Fulvio Magni, Silvia Garagna et al.
      Pages 43-47

  4. Predictive Modelling

    1. Front Matter

      Pages 49-49
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    2. Predicting Kidney Transplant Survival Using Multiple Feature Representations for HLAs

      • Mohammadreza Nemati, Haonan Zhang, Michael Sloma, Dulat Bekbolsynov, Hong Wang, Stanislaw Stepkowski et al.
      Pages 51-60

    3. Sum-Product Networks for Early Outbreak Detection of Emerging Diseases

      • Moritz Kulessa, Bennet Wittelsbach, Eneldo Loza Mencía, Johannes Fürnkranz
      Pages 61-71

    4. Catching Patient’s Attention at the Right Time to Help Them Undergo Behavioural Change: Stress Classification Experiment from Blood Volume Pulse

      • Aneta Lisowska, Szymon Wilk, Mor Peleg
      Pages 72-82

    5. Primary Care Datasets for Early Lung Cancer Detection: An AI Led Approach

      • Goce Ristanoski, Jon Emery, Javiera Martinez Gutierrez, Damien McCarthy, Uwe Aickelin
      Pages 83-92

    6. Addressing Extreme Imbalance for Detecting Medications Mentioned in Twitter User Timelines

      • Davy Weissenbacher, Siddharth Rawal, Arjun Magge, Graciela Gonzalez-Hernandez
      Pages 93-102

    7. ICU Days-to-Discharge Analysis with Machine Learning Technology

      • David Cuadrado, David Riaño
      Pages 103-113

    8. Transformers for Multi-label Classification of Medical Text: An Empirical Comparison

      • Vithya Yogarajan, Jacob Montiel, Tony Smith, Bernhard Pfahringer
      Pages 114-123

    9. Semantic Web Framework to Computerize Staged Reflex Testing Protocols to Mitigate Underutilization of Pathology Tests for Diagnosing Pituitary Disorders

      • William Van Woensel, Manal Elnenaei, Syed Ali Imran, Syed Sibte Raza Abidi
      Pages 124-134

    10. Using Distribution Divergence to Predict Changes in the Performance of Clinical Predictive Models

      • Mohammadamin Tajgardoon, Shyam Visweswaran
      Pages 135-145

    11. Analysis of Health Screening Records Using Interpretations of Predictive Models

      • Yuki Oba, Taro Tezuka, Masaru Sanuki, Yukiko Wagatsuma
      Pages 146-151

    12. Seasonality in Infection Predictions Using Interpretable Models for High Dimensional Imbalanced Datasets

      • Bernardo Cánovas-Segura, Antonio Morales, Jose M. Juárez, Manuel Campos
      Pages 152-156
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About this book

This book constitutes the refereed proceedings of the 19th International Conference on Artificial Intelligence in Medicine, AIME 2021, held as a virtual event, in June 2021.

The 28 full papers presented together with 30 short papers were selected from 138 submissions. The papers are grouped in topical sections on image analysis; predictive modelling; temporal data analysis; unsupervised learning; planning and decision support; deep learning; natural language processing; and knowledge representation and rule mining.

Editors and Affiliations

  • Brunel University London, Uxbridge, UK

    Allan Tucker

  • University of Coimbra, Coimbra, Portugal

    Pedro Henriques Abreu

  • University of Porto, Porto, Portugal

    Jaime Cardoso, Pedro Pereira Rodrigues

  • Universitat Rovira i Virgili, Tarragona, Spain

    David Riaño

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