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Predictive Intelligence in Medicine [electronic resource] : 5th International Workshop, PRIME 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings /

Contributor(s): Material type: TextTextSeries: Lecture Notes in Computer Science ; 13564Publisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2022Edition: 1st ed. 2022Description: XI, 213 p. 70 illus., 62 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783031169199
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 006.3 23
LOC classification:
  • Q334-342
  • TA347.A78
Online resources:
Contents:
Federated Time-dependent GNN Learning from Brain Connectivity Data with Missing Timepoints -- Bridging the Gap between Deep Learning and Hypothesis-Driven Analysis via Permutation Testing -- Multi-Tracer PET Imaging Using Deep Learning: Applications in Patients with High-Grade Gliomas -- Multiple Instance Neuroimage Transformer -- Intervertebral Disc Labeling With Learning Shape Information, A Look Once Approach -- Mixup augmentation improves age prediction from T1-weighted brain MRI scans -- Diagnosing Knee Injuries from MRI with Transformer Based Deep Learning -- MISS-Net: Multi-view contrastive transformer network for MCI stages prediction using brain 18F-FDG PET imaging -- TransDeepLab: Convolution-Free Transformer-based DeepLab v3+ for Medical Image Segmentation -- Opportunistic hip fracture risk prediction in Men from X-ray: Findings from the Osteoporosis in Men (MrOS) Study -- Weakly-Supervised TILs Segmentation based on Point Annotations using Transfer Learning with Point Detector and Projected-Boundary Regressor -- Discriminative Deep Neural Network for Predicting Knee OsteoArthritis in Early Stage -- Long-Term Cognitive Outcome Prediction in Stroke Patients Using Multi-Task Learning on Imaging and Tabular Data -- Quantifying the Predictive Uncertainty of Regression GNN Models Under Target Domain Shifts -- Investigating the Predictive Reproducibility of Federated Graph Neural Networks using Medical Datasets -- Learning subject-specific functional parcellations from cortical surface measures -- A Triplet Contrast Learning of Global and Local Representations for Unannotated Medical Images -- Predicting Brain Multigraph Population From a Single Graph Template for Boosting One-Shot Classification -- Meta-RegGNN: Predicting Verbal and Full-Scale Intelligence Scores using Graph Neural Networks and Meta-Learning.
In: Springer Nature eBookSummary: This book constitutes the proceedings of the 5th International Workshop on Predictive Intelligence in Medicine, PRIME 2022, held in conjunction with MICCAI 2022 as a hybrid event in Singapore, in September 2022. The 19 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.
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Federated Time-dependent GNN Learning from Brain Connectivity Data with Missing Timepoints -- Bridging the Gap between Deep Learning and Hypothesis-Driven Analysis via Permutation Testing -- Multi-Tracer PET Imaging Using Deep Learning: Applications in Patients with High-Grade Gliomas -- Multiple Instance Neuroimage Transformer -- Intervertebral Disc Labeling With Learning Shape Information, A Look Once Approach -- Mixup augmentation improves age prediction from T1-weighted brain MRI scans -- Diagnosing Knee Injuries from MRI with Transformer Based Deep Learning -- MISS-Net: Multi-view contrastive transformer network for MCI stages prediction using brain 18F-FDG PET imaging -- TransDeepLab: Convolution-Free Transformer-based DeepLab v3+ for Medical Image Segmentation -- Opportunistic hip fracture risk prediction in Men from X-ray: Findings from the Osteoporosis in Men (MrOS) Study -- Weakly-Supervised TILs Segmentation based on Point Annotations using Transfer Learning with Point Detector and Projected-Boundary Regressor -- Discriminative Deep Neural Network for Predicting Knee OsteoArthritis in Early Stage -- Long-Term Cognitive Outcome Prediction in Stroke Patients Using Multi-Task Learning on Imaging and Tabular Data -- Quantifying the Predictive Uncertainty of Regression GNN Models Under Target Domain Shifts -- Investigating the Predictive Reproducibility of Federated Graph Neural Networks using Medical Datasets -- Learning subject-specific functional parcellations from cortical surface measures -- A Triplet Contrast Learning of Global and Local Representations for Unannotated Medical Images -- Predicting Brain Multigraph Population From a Single Graph Template for Boosting One-Shot Classification -- Meta-RegGNN: Predicting Verbal and Full-Scale Intelligence Scores using Graph Neural Networks and Meta-Learning.

This book constitutes the proceedings of the 5th International Workshop on Predictive Intelligence in Medicine, PRIME 2022, held in conjunction with MICCAI 2022 as a hybrid event in Singapore, in September 2022. The 19 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.

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