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Predictive Intelligence in Medicine

6th International Workshop, PRIME 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Islem Rekik

    1. Imperial College London, London, UK

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  2. Ehsan Adeli

    1. Stanford University, Stanford, USA

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  3. Sang Hyun Park

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

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  4. Celia Cintas

    1. IBM Research - Africa, Nairobi, Kenya

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  5. Ghada Zamzmi

    1. United States Food and Drug Administration, Silver Spring, USA

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14277)

Included in the following conference series:

Conference proceedings info: PRIME 2023.

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About this book

This volume LNCS 14277 constitutes the refereed proceedings of the 6th International Workshop, PRIME 2023, Held in Conjunction with MICCAI 2023, in October 2023, held in Vancouver, BC, Canada.

The 24 full papers presented were carefully reviewed and selected from 27 submissions. This workshop intersects ideas from both machine learning and mathematical/statistical/physical modeling research directions in the hope to provide a deeper understanding of the foundations of predictive intelligence developed for medicine, as well as to where we currently stand and what we aspire to achieve through this field. 




Keywords

Table of contents (24 papers)

  1. Front Matter

    Pages i-xiii
    Download chapter PDF

  2. Longitudinal Self-supervised Learning Using Neural Ordinary Differential Equation

    • Rachid Zeghlache, Pierre-Henri Conze, Mostafa El Habib Daho, Yihao Li, Hugo Le Boité, Ramin Tadayoni et al.
    Pages 1-13

  3. Template-Based Federated Multiview Domain Alignment for Predicting Heterogeneous Brain Graph Evolution Trajectories from Baseline

    • Emircan Gündoğdu, Islem Rekik
    Pages 14-24

  4. Feature-Based Transformer with Incomplete Multimodal Brain Images for Diagnosis of Neurodegenerative Diseases

    • Xingyu Gao, Feng Shi, Dinggang Shen, Manhua Liu
    Pages 25-34

  5. RepNet for Quantifying the Reproducibility of Graph Neural Networks in Multiview Brain Connectivity Biomarker Discovery

    • Hizir Can Bayram, Mehmet Serdar Çelebi, Islem Rekik
    Pages 35-45

  6. SynthA1c: Towards Clinically Interpretable Patient Representations for Diabetes Risk Stratification

    • Michael S. Yao, Allison Chae, Matthew T. MacLean, Anurag Verma, Jeffrey Duda, James C. Gee et al.
    Pages 46-57

  7. Confounding Factors Mitigation in Brain Age Prediction Using MRI with Deformation Fields

    • K. H. Aqil, Tanvi Kulkarni, Jaikishan Jayakumar, Keerthi Ram, Mohanasankar Sivaprakasam
    Pages 58-69

  8. Self-supervised Landmark Learning with Deformation Reconstruction and Cross-Subject Consistency Objectives

    • Chun-Hung Chao, Marc Niethammer
    Pages 70-82

  9. DAE-Former: Dual Attention-Guided Efficient Transformer for Medical Image Segmentation

    • Reza Azad, René Arimond, Ehsan Khodapanah Aghdam, Amirhossein Kazerouni, Dorit Merhof
    Pages 83-95

  10. Diffusion-Based Graph Super-Resolution with Application to Connectomics

    • Nishant Rajadhyaksha, Islem Rekik
    Pages 96-107

  11. Deep Survival Analysis in Multiple Sclerosis

    • Xin Zhang, Deval Mehta, Chao Zhu, Daniel Merlo, Yanan Hu, Melissa Gresle et al.
    Pages 108-119

  12. Federated Multi-trajectory GNNs Under Data Limitations for Baby Brain Connectivity Forecasting

    • Michalis Pistos, Gang Li, Weili Lin, Dinggang Shen, Islem Rekik
    Pages 120-133

  13. Learning Task-Specific Morphological Representation for Pyramidal Cells via Mutual Information Minimization

    • Chunli Sun, Qinghai Guo, Gang Yang, Feng Zhao
    Pages 134-145

  14. DermoSegDiff: A Boundary-Aware Segmentation Diffusion Model for Skin Lesion Delineation

    • Afshin Bozorgpour, Yousef Sadegheih, Amirhossein Kazerouni, Reza Azad, Dorit Merhof
    Pages 146-158

  15. Self-supervised Few-Shot Learning for Semantic Segmentation: An Annotation-Free Approach

    • Sanaz Karimijafarbigloo, Reza Azad, Dorit Merhof
    Pages 159-171

  16. Imputing Brain Measurements Across Data Sets via Graph Neural Networks

    • Yixin Wang, Wei Peng, Susan F. Tapert, Qingyu Zhao, Kilian M. Pohl
    Pages 172-183

  17. Multi-input Vision Transformer with Similarity Matching

    • Seungeun Lee, Sung Ho Hwang, Saelin Oh, Beom Jin Park, Yongwon Cho
    Pages 184-193

  18. Federated Multi-domain GNN Network for Brain Multigraph Generation

    • Chun Xu, Islem Rekik
    Pages 194-205

  19. An Ambient Intelligence-Based Approach for Longitudinal Monitoring of Verbal and Vocal Depression Symptoms

    • Alice Othmani, Muhammad Muzammel
    Pages 206-217

  20. Dynamic Depth-Supervised NeRF for Multi-view RGB-D Operating Room Videos

    • Beerend G. A. Gerats, Jelmer M. Wolterink, Ivo A. M. J. Broeders
    Pages 218-230
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Other volumes

  1. Predictive Intelligence in Medicine

Editors and Affiliations

  • Imperial College London, London, UK

    Islem Rekik

  • Stanford University, Stanford, USA

    Ehsan Adeli

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

    Sang Hyun Park

  • IBM Research - Africa, Nairobi, Kenya

    Celia Cintas

  • United States Food and Drug Administration, Silver Spring, USA

    Ghada Zamzmi

Bibliographic Information

  • Book Title: Predictive Intelligence in Medicine

  • Book Subtitle: 6th International Workshop, PRIME 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings

  • Editors: Islem Rekik, Ehsan Adeli, Sang Hyun Park, Celia Cintas, Ghada Zamzmi

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-031-46005-0

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023

  • Softcover ISBN: 978-3-031-46004-3Published: 07 October 2023

  • eBook ISBN: 978-3-031-46005-0Published: 07 October 2023

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XIII, 294

  • Number of Illustrations: 3 b/w illustrations, 94 illustrations in colour

  • Topics: Artificial Intelligence

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