Search Results for author:
Found 2 papers, 2 papers with code
TLDR at SemEval-2024 Task 2: T5-generated clinical-Language summaries for DeBERTa Report Analysis
This paper introduces novel methodologies for the Natural Language Inference for Clinical Trials (NLI4CT) task.
Temporal Supervised Contrastive Learning for Modeling Patient Risk Progression
To solve this problem, we propose a supervised contrastive learning framework that learns an embedding representation for each time step of a patient time series.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
