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Predictive Intelligence in Medicine : 4th International Workshop, PRIME 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings / edited by Islem Rekik, Ehsan Adeli, Sang Hyun Park, Julia Schnabel.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 12928
- Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12928
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Image processing-Digital techniques.
- Computer vision.
- Computer engineering.
- Computer networks.
- Bioinformatics.
- Artificial Intelligence.
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Computer Engineering and Networks.
- Computational and Systems Biology.
- Local Subjects:
- Artificial Intelligence.
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Computer Engineering and Networks.
- Computational and Systems Biology.
- Physical Description:
- 1 online resource (XIII, 280 pages) : 80 illustrations, 68 illustrations in color.
- Edition:
- 1st ed. 2021.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2021.
- System Details:
- text file PDF
- Summary:
- This book constitutes the proceedings of the 4th International Workshop on Predictive Intelligence in Medicine, PRIME 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in October 2021.* The 25 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. *The workshop was held virtually.
- Contents:
- Self-Supervised Learning based CT Denoising using Pseudo-CT Image Pairs
- A Few-shot Learning Graph Multi-Trajectory Evolution Network for Forecasting Multimodal Baby Connectivity Development from a Baseline Timepoint
- One Representative-Shot Learning Using a Population-Driven Template with Application to Brain Connectivity Classification and Evolution Prediction
- Mixing-AdaSIN: Constructing a De-biased Dataset using Adaptive Structural Instance Normalization and Texture Mixing
- Liver Tumor Localization and Characterization from Multi-Phase MR Volumes Using Key-Slice Prediction: A Physician-Inspired Approach
- Improving Tuberculosis Recognition on Bone-Suppressed Chest X-rays Guided by Task-Specific Features
- Template-Based Inter-modality Super-resolution of Brain Connectivity
- Adversarial Bayesian Optimization for Quantifying Motion Artifact within MRI
- False Positive Suppression in Cervical Cell Screening via Attention-Guided Semi-Supervised Learning
- Investigating and Quantifying the Reproducibility of Graph Neural Networks in Predictive Medicine
- Self Supervised Contrastive Learning on Multiple Breast Modalities Boosts Classification Performance
- Self-Guided Multi-Attention Network for Periventricular Leukomalacia Recognition
- Opportunistic Screening of Osteoporosis Using Plain Film Chest X-ray
- Multi-Task Deep Segmentation and Radiomics for Automatic Prognosis in Head and Neck Cancer
- Integrating Multimodal MRIs for Adult ADHD Identification with Heterogeneous Graph Attention Convolutional Network
- Probabilistic Deep Learning with Adversarial Training and Volume Interval Estimation - Better Ways to Perform and Evaluate Predictive Models for White Matter Hyperintensities Evolution
- A Multi-scale Capsule Network for Improving Diagnostic Generalizability in Breast Cancer Diagnosis using Ultrasonography
- Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy using Multi-scale Patch Learning with Mammography
- The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification
- Anatomical Structure-aware Pulmonary Nodule Detection via Parallel Multi-Task RoI Head
- Towards Cancer Patients Classification Using Liquid Biopsy
- Foreseeing Survival through `Fuzzy Intelligence': A cognitively-inspired incremental learning based de novo model for Breast Cancer Prognosis by multi-omics data fusion
- Improving Across Dataset Brain Age Predictions using Transfer Learning
- Uncertainty-Based Dynamic Graph Neighborhoods For Medical Segmentation
- FLAT-Net: Longitudinal Brain Graph Evolution Prediction from a Few Training Representative Templates.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-87602-9
- 9783030876029
- Access Restriction:
- Restricted for use by site license.
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