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Predictive Intelligence in Medicine: 5th International Workshop, PRIME 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings: Lecture Notes in Computer Science, cartea 13564

Editat de Islem Rekik, Ehsan Adeli, Sang Hyun Park, Celia Cintas
en Limba Engleză Paperback – 21 sep 2022
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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Specificații

ISBN-13: 9783031169182
ISBN-10: 3031169182
Pagini: 213
Ilustrații: XI, 213 p. 70 illus., 62 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.33 kg
Ediția:1st ed. 2022
Editura: Springer Nature Switzerland
Colecția Springer
Seria Lecture Notes in Computer Science

Locul publicării:Cham, Switzerland

Cuprins

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