Predictive Intelligence in Medicine : 5th International Workshop, PRIME 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings / / edited by Islem Rekik, Ehsan Adeli, Sang Hyun Park, Celia Cintas

• Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2022
• Edizione: 1st ed. 2022.
• Descrizione fisica: 1 online resource (224 pages)
• Disciplina: 060; 610.28563
• Soggetto topico: Artificial intelligence; Computer engineering; Computer networks; Computers; Application software; Artificial Intelligence; Computer Engineering and Networks; Computing Milieux; Computer and Information Systems Applications
• Persona (resp. second.): RekikIslem
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: 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.
• Sommario/riassunto: 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.
• Titolo autorizzato: Predictive Intelligence in Medicine
• ISBN: 9783031169199; 3031169190
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910595048703321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Computer Science, . 1611-3349 ; ; 13564