|
|
|
|
LEADER |
03828nmm a2200397 u 4500 |
001 |
EB002091724 |
003 |
EBX01000000000000001231816 |
005 |
00000000000000.0 |
007 |
cr||||||||||||||||||||| |
008 |
221004 ||| eng |
020 |
|
|
|a 9783031169199
|
100 |
1 |
|
|a Rekik, Islem
|e [editor]
|
245 |
0 |
0 |
|a Predictive Intelligence in Medicine
|h Elektronische Ressource
|b 5th International Workshop, PRIME 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings
|c edited by Islem Rekik, Ehsan Adeli, Sang Hyun Park, Celia Cintas
|
250 |
|
|
|a 1st ed. 2022
|
260 |
|
|
|a Cham
|b Springer Nature Switzerland
|c 2022, 2022
|
300 |
|
|
|a XI, 213 p. 70 illus., 62 illus. in color
|b online resource
|
505 |
0 |
|
|a 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
|
653 |
|
|
|a Artificial Intelligence
|
653 |
|
|
|a Computers
|
653 |
|
|
|a Application software
|
653 |
|
|
|a Computer networks
|
653 |
|
|
|a Computer Engineering and Networks
|
653 |
|
|
|a Artificial intelligence
|
653 |
|
|
|a Computer engineering
|
653 |
|
|
|a Computer and Information Systems Applications
|
653 |
|
|
|a Computing Milieux
|
700 |
1 |
|
|a Adeli, Ehsan
|e [editor]
|
700 |
1 |
|
|a Park, Sang Hyun
|e [editor]
|
700 |
1 |
|
|a Cintas, Celia
|e [editor]
|
041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
989 |
|
|
|b Springer
|a Springer eBooks 2005-
|
490 |
0 |
|
|a Lecture Notes in Computer Science
|
028 |
5 |
0 |
|a 10.1007/978-3-031-16919-9
|
856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-031-16919-9?nosfx=y
|x Verlag
|3 Volltext
|
082 |
0 |
|
|a 006.3
|
520 |
|
|
|a 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
|