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Found 6 papers, 2 papers with code
Comparing Encoder-Only and Encoder-Decoder Transformers for Relation Extraction from Biomedical Texts: An Empirical Study on Ten Benchmark Datasets
Biomedical relation extraction, aiming to automatically discover high-quality and semantic relations between the entities from free text, is becoming a vital step for automated knowledge discovery.
Evidence-based Fact-Checking of Health-related Claims
Our experiments showed that training deep learning models on real-world medical claims greatly improves performance compared to models trained on synthetic and open-domain claims.
NLM at MEDIQA 2021: Transfer Learning-based Approaches for Consumer Question and Multi-Answer Summarization
One of the cardinal tasks in achieving robust consumer health question answering systems is the question summarization and multi-document answer summarization.
Contributions to the Improvement of Question Answering Systems in the Biomedical Domain
In our first contribution, we propose a machine learning-based method for question type classification to determine the types of given questions which enable to a biomedical QA system to use the appropriate answer extraction method.
Visual Question Generation from Radiology Images
Visual Question Generation (VQG), the task of generating a question based on image contents, is an increasingly important area that combines natural language processing and computer vision.
A Biomedical Question Answering System in BioASQ 2017
Question answering, the identification of short accurate answers to users questions, is a longstanding challenge widely studied over the last decades in the open domain.
