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Artificial Intelligence in Medicine

18th International Conference on Artificial Intelligence in Medicine, AIME 2020, Minneapolis, MN, USA, August 25–28, 2020, Proceedings

  • Conference proceedings
  • © 2020

Overview

Editors:
  1. Martin Michalowski

    1. School of Nursing, University of Minnesota, Minneapolis, USA

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    You can also search for this editor in PubMed   Google Scholar

  2. Robert Moskovitch

    1. Ben-Gurion University of the Negev, Tonawanda, USA

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12299)

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

Included in the following conference series:

Conference proceedings info: AIME 2020.

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Table of contents (44 papers)

  1. Front Matter

    Pages i-xix
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  2. Deep Learning

    1. Front Matter

      Pages 1-1
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    2. All-Cause Mortality Prediction in T2D Patients

      • Pavel Novitski, Cheli Melzer Cohen, Avraham Karasik, Varda Shalev, Gabriel Hodik, Robert Moskovitch
      Pages 3-13

    3. Heterogeneous Graph Embeddings of Electronic Health Records Improve Critical Care Disease Predictions

      • Tingyi Wanyan, Martin Kang, Marcus A. Badgeley, Kipp W. Johnson, Jessica K. De Freitas, Fayzan F. Chaudhry et al.
      Pages 14-25

    4. Controlling Level of Unconsciousness by Titrating Propofol with Deep Reinforcement Learning

      • Gabriel Schamberg, Marcus Badgeley, Emery N. Brown
      Pages 26-36

    5. SMOOTH-GAN: Towards Sharp and Smooth Synthetic EHR Data Generation

      • Sina Rashidian, Fusheng Wang, Richard Moffitt, Victor Garcia, Anurag Dutt, Wei Chang et al.
      Pages 37-48

    6. A Multi-task LSTM Framework for Improved Early Sepsis Prediction

      • Theodoros Tsiligkaridis, Jennifer Sloboda
      Pages 49-58

    7. Deep Learning Applied to Blood Glucose Prediction from Flash Glucose Monitoring and Fitbit Data

      • Pietro Bosoni, Marco Meccariello, Valeria Calcaterra, Cristiana Larizza, Lucia Sacchi, Riccardo Bellazzi
      Pages 59-63

  3. Natural Language Processing

    1. Front Matter

      Pages 65-65
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    2. Comparing NLP Systems to Extract Entities of Eligibility Criteria in Dietary Supplements Clinical Trials Using NLP-ADAPT

      • Anusha Bompelli, Greg Silverman, Raymond Finzel, Jake Vasilakes, Benjamin Knoll, Serguei Pakhomov et al.
      Pages 67-77

    3. Ontology-Guided Data Augmentation for Medical Document Classification

      • Mahdi Abdollahi, Xiaoying Gao, Yi Mei, Shameek Ghosh, Jinyan Li
      Pages 78-88

    4. Divide to Better Classify

      • Yves Mercadier, Jérôme Azé, Sandra Bringay
      Pages 89-99

    5. Automatic Breast Cancer Cohort Detection from Social Media for Studying Factors Affecting Patient-Centered Outcomes

      • Mohammed Ali Al-Garadi, Yuan-Chi Yang, Sahithi Lakamana, Jie Lin, Sabrina Li, Angel Xie et al.
      Pages 100-110

    6. Predicting Clinical Diagnosis from Patients Electronic Health Records Using BERT-Based Neural Networks

      • Pavel Blinov, Manvel Avetisian, Vladimir Kokh, Dmitry Umerenkov, Alexander Tuzhilin
      Pages 111-121

    7. Drug-Drug Interaction Prediction on a Biomedical Literature Knowledge Graph

      • Konstantinos Bougiatiotis, Fotis Aisopos, Anastasios Nentidis, Anastasia Krithara, Georgios Paliouras
      Pages 122-132

    8. AI Medical School Tutor: Modelling and Implementation

      • Shazia Afzal, Tejas Indulal Dhamecha, Paul Gagnon, Akash Nayak, Ayush Shah, Jan Carlstedt-Duke et al.
      Pages 133-145

  4. Predictive Modeling

    1. Front Matter

      Pages 147-147
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    2. Lung Cancer Survival Prediction Using Instance-Specific Bayesian Networks

      • Fattaneh Jabbari, Liza C. Villaruz, Mike Davis, Gregory F. Cooper
      Pages 149-159

    3. Development and Preliminary Evaluation of a Method for Passive, Privacy-Aware Home Care Monitoring Based on 2D LiDAR Data

      • Paolo Fraccaro, Xenophon Evangelopoulos, Blair Edwards
      Pages 160-169

    4. Innovative Method to Build Robust Prediction Models When Gold-Standard Outcomes Are Scarce

      • Ying Zhu, Roshan Tourani, Adam Sheka, Elizabeth Wick, Genevieve B. Melton, Gyorgy Simon
      Pages 170-180
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Other volumes

  1. Artificial Intelligence in Medicine

Keywords

About this book

The LNAI 12299 constitutes the papers of the 18th International Conference on Artificial Intelligence in Medicine, AIME 2020, which will be held online in August 2020.

 

The 42 full papers presented together with 1short papers in this volume were carefully reviewed and selected from a total of 103 submissions.

 

The AIME 2020 goals were to present and consolidate the international state of the art of AI in biomedical research from the perspectives of theory, methodology, systems, and applications.

Editors and Affiliations

  • School of Nursing, University of Minnesota, Minneapolis, USA

    Martin Michalowski

  • Ben-Gurion University of the Negev, Tonawanda, USA

    Robert Moskovitch

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