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Predictive Intelligence in Medicine

Second International Workshop, PRIME 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings

  • Conference proceedings
  • © 2019

Overview

Editors:
  1. Islem Rekik

    1. BASIRA, Istanbul Technical University, Istanbul, Turkey

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    You can also search for this editor in PubMed   Google Scholar

  2. Ehsan Adeli

    1. Stanford University, Stanford, USA

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    You can also search for this editor in PubMed   Google Scholar

  3. Sang Hyun Park

    1. Daegu Gyeongbuk Institute of Science and Technology, Daegu, Korea (Republic of)

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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 11843)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

Included in the following conference series:

Conference proceedings info: PRIME 2019.

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Table of contents (19 papers)

  1. Front Matter

    Pages i-xiii
    Download chapter PDF

  2. TADPOLE Challenge: Accurate Alzheimer’s Disease Prediction Through Crowdsourced Forecasting of Future Data

    • Răzvan V. Marinescu, Neil P. Oxtoby, Alexandra L. Young, Esther E. Bron, Arthur W. Toga, Michael W. Weiner et al.
    Pages 1-10

  3. Inter-fractional Respiratory Motion Modelling from Abdominal Ultrasound: A Feasibility Study

    • Alina Giger, Christoph Jud, Damien Nguyen, Miriam Krieger, Ye Zhang, Antony J. Lomax et al.
    Pages 11-22

  4. Adaptive Neuro-Fuzzy Inference System-Based Chaotic Swarm Intelligence Hybrid Model for Recognition of Mild Cognitive Impairment from Resting-State fMRI

    • Ahmed M. Anter, Zhiguo Zhang
    Pages 23-33

  5. Deep Learning via Fused Bidirectional Attention Stacked Long Short-Term Memory for Obsessive-Compulsive Disorder Diagnosis and Risk Screening

    • Chiyu Feng, Lili Jin, Chuangyong Xu, Peng Yang, Tianfu Wang, Baiying Lei et al.
    Pages 34-43

  6. Modeling Disease Progression in Retinal OCTs with Longitudinal Self-supervised Learning

    • Antoine Rivail, Ursula Schmidt-Erfurth, Wolf-Dieter Vogl, Sebastian M. Waldstein, Sophie Riedl, Christoph Grechenig et al.
    Pages 44-52

  7. Predicting Response to the Antidepressant Bupropion Using Pretreatment fMRI

    • Kevin P. Nguyen, Cherise Chin Fatt, Alex Treacher, Cooper Mellema, Madhukar H. Trivedi, Albert Montillo
    Pages 53-62

  8. Progressive Infant Brain Connectivity Evolution Prediction from Neonatal MRI Using Bidirectionally Supervised Sample Selection

    • Olfa Ghribi, Gang Li, Weili Lin, Dinggang Shen, Islem Rekik
    Pages 63-72

  9. Computed Tomography Image-Based Deep Survival Regression for Metastatic Colorectal Cancer Using a Non-proportional Hazards Model

    • Alexander Katzmann, Alexander Mühlberg, Michael Sühling, Dominik Nörenberg, Stefan Maurus, Julian Walter Holch et al.
    Pages 73-80

  10. 7 Years of Developing Seed Techniques for Alzheimer’s Disease Diagnosis Using Brain Image and Connectivity Data Largely Bypassed Prediction for Prognosis

    • Mayssa Soussia, Islem Rekik
    Pages 81-93

  11. Generative Adversarial Irregularity Detection in Mammography Images

    • Milad Ahmadi, Mohammad Sabokrou, Mahmood Fathy, Reza Berangi, Ehsan Adeli
    Pages 94-104

  12. Hierarchical Adversarial Connectomic Domain Alignment for Target Brain Graph Prediction and Classification from a Source Graph

    • Alaa Bessadok, Mohamed Ali Mahjoub, Islem Rekik
    Pages 105-114

  13. Predicting High-Resolution Brain Networks Using Hierarchically Embedded and Aligned Multi-resolution Neighborhoods

    • Kübra Cengiz, Islem Rekik
    Pages 115-124

  14. Catheter Synthesis in X-Ray Fluoroscopy with Generative Adversarial Networks

    • Ihsan Ullah, Philip Chikontwe, Sang Hyun Park
    Pages 125-133

  15. Prediction of Clinical Scores for Subjective Cognitive Decline and Mild Cognitive Impairment

    • Aojie Li, Ling Yue, Manhua Liu, Shifu Xiao
    Pages 134-141

  16. Diagnosis of Parkinson’s Disease in Genetic Cohort Patients via Stage-Wise Hierarchical Deep Polynomial Ensemble Learning

    • Haijun Lei, Hancong Li, Ahmed Elazab, Xuegang Song, Zhongwei Huang, Baiying Lei
    Pages 142-150

  17. Automatic Detection of Bowel Disease with Residual Networks

    • Robert Holland, Uday Patel, Phillip Lung, Elisa Chotzoglou, Bernhard Kainz
    Pages 151-159

  18. Support Vector Based Autoregressive Mixed Models of Longitudinal Brain Changes and Corresponding Genetics in Alzheimer’s Disease

    • Qifan Yang, Sophia I. Thomopoulos, Linda Ding, Wesley Surento, Paul M. Thompson, Neda Jahanshad et al.
    Pages 160-167

  19. Treatment Response Prediction of Hepatocellular Carcinoma Patients from Abdominal CT Images with Deep Convolutional Neural Networks

    • Hansang Lee, Helen Hong, Jinsil Seong, Jin Sung Kim, Junmo Kim
    Pages 168-176

  20. Correction to: Modeling Disease Progression in Retinal OCTs with Longitudinal Self-supervised Learning

    • Antoine Rivail, Ursula Schmidt-Erfurth, Wolf-Dieter Vogl, Sebastian M. Waldstein, Sophie Riedl, Christoph Grechenig et al.
    Pages C1-C1
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Other volumes

  1. Predictive Intelligence in Medicine

Keywords

About this book

This book constitutes the proceedings of the Second International Workshop on Predictive Intelligence in Medicine, PRIME 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. 
The 18 papers presented in this volume were carefully reviewed and selected for inclusion in this book. The contributions describe new cutting-edge predictive models and methods that solve challenging problems in the medical field for a high-precision predictive medicine. 

Editors and Affiliations

  • BASIRA, Istanbul Technical University, Istanbul, Turkey

    Islem Rekik

  • Stanford University, Stanford, USA

    Ehsan Adeli

  • Daegu Gyeongbuk Institute of Science and Technology, Daegu, Korea (Republic of)

    Sang Hyun Park

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