Predictive Intelligence in Medicine by Rekik, Islem; Adeli, Ehsan; Park, Sang Hyun; Schnabel, Julia;

Hosszú leírás:

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.

Tartalomjegyzék:

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 SampleSelection: 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.