1 citations · 1 across the 5 of their papers we have counts for
5 papers
Bootstrapped Physically-Primed Neural Networks for Robust T2 Distribution Estimation in Low-SNR Pancreatic MRI
Hadas Ben Atya, Nicole Abramenkov, Noa Mashiah +4
Estimating multi-component T2 relaxation distributions from Multi-Echo Spin Echo (MESE) MRI is a severely ill-posed inverse problem, traditionally solved using regularized non-nega…
Hierarchical Section Matching Prediction (HSMP) BERT for Fine-Grained Extraction of Structured Data from Hebrew Free-Text Radiology Reports in Crohn's Disease
Zvi Badash, Hadas Ben-Atya, Naama Gavrielov +6
Extracting structured clinical information from radiology reports is challenging, especially in low-resource languages. This is pronounced in Crohn's disease, with sparsely represe…
Agent-Based Uncertainty Awareness Improves Automated Radiology Report Labeling with an Open-Source Large Language Model
Hadas Ben-Atya, Naama Gavrielov, Zvi Badash +5
Reliable extraction of structured data from radiology reports using Large Language Models (LLMs) remains challenging, especially for complex, non-English texts like Hebrew. This st…
P2T2: a Physically-primed deep-neural-network approach for robust distribution estimation from quantitative -weighted MRI
Hadas Ben-Atya, Moti Freiman
Estimating relaxation time distributions from multi-echo -weighted MRI () data can provide valuable biomarkers for assessing inflammation, demyelination, edema, an…
Rethinking The Memory Staleness Problem In Dynamics GNN
Mor Ventura, Hadas Ben Atya, Dekel Brav
The staleness problem is a well-known problem when working with dynamic data, due to the absence of events for a long time. Since the memory of the node is updated only when the no…