Overview

This volume constitutes the refereed proceedings of the 7th International Workshop on Predictive Intelligence in Medicine, PRIME 2024, held in conjunction with the 27th International conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024, in Marrakesh, Morocco in October 2024. The 17 full papers presented here were carefully reviewed and selected from 22 submissions. These papers focus on the current, cutting-edge Predictive models and methods with applications in the field of Medical data analysis, for early disease prediction and prevention. 

Full Product Details

Author:   Islem Rekik ,  Ehsan Adeli ,  Sang Hyun Park ,  Celia Cintas
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   2024 ed.
Volume:   15155
ISBN:  

9783031745607

ISBN 10:   3031745604
Pages:   208
Publication Date:   18 October 2024
Audience:   Professional and scholarly ,  College/higher education ,  Professional & Vocational ,  Postgraduate, Research & Scholarly
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
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Table of Contents

Modelling the Neonatal Brain Development Using Implicit Neural Representations.- Attention Based Features Fusion Emotion Guided fNIRS Classification Network for Prenatal Depression Recognition.- Spectral Graph Sample Weighting for Interpretable Sub cohort Analysis in Predictive Models for Neuroimaging.- RCT Relational Connectivity Transformer for Enhanced Prediction of Absolute and Residual Intelligence.- Gene to Image Decoding Brain Images from Genetics via Latent Diffusion Models.- Physics Guided Multi View Graph Neural Network for Schizophrenia Classification via Structural Functional Coupling.- Automated Patient Specific Pneumoperitoneum Model Reconstruction for Surgical Navigation Systems in Distal Gastrectomy.- MNA net Multimodal Neuroimaging Attention based Architecture for Cognitive Decline Prediction.- Improving Brain MRI Segmentation with Multi Stage Deep Domain Unlearning.- DynGNN Dynamic Memory enhanced Generative GNNs for Predicting Temporal Brain Connectivity.- Strongly Topology preserving GNNs for Brain Graph Super resolution.- Generative Hypergraph Neural Network for Multiview Brain Connectivity Fusion.- Identifying brain ageing trajectories using variational autoencoders with regression model in neuroimaging data stratified by sex and validated against dementia related risk factors.- Integrating Deep Learning with Fundus and Optical Coherence Tomography for Cardiovascular Disease Prediction.- Self-Supervised Contrastive Learning for Consistent Few Shot Image Representations.- Neurocognitive Latent Space Regularization for Multi Label Diagnosis from MRI.- Segmentation of Brain Metastases in MRI A Two Stage Deep Learning Approach with Modality Impact Study.

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