Electronic health records (EHR) contain vast biomedical knowledge and ar...
Entities lie in the heart of biomedical natural language understanding, ...
Pretrained language models have served as important backbones for natura...
Term clustering is important in biomedical knowledge graph construction....
Biomedical knowledge graphs (BioMedKGs) are essential infrastructures fo...
Objective: Disease knowledge graphs are a way to connect, organize, and
...
Entity alignment (EA) merges knowledge graphs (KGs) by identifying the
e...
Knowledge graph integration typically suffers from the widely existing
d...
We present PMC-Patients, a dataset consisting of 167k patient notes with...
The medical automatic diagnosis system aims to imitate human doctors in ...
The existing neural machine translation system has achieved near human-l...
Question Answering (QA) is a benchmark Natural Language Processing (NLP)...
We propose a novel medical term embedding method named CODER, which stan...
Objective: Medical relations are the core components of medical knowledg...
Machine learning (ML) and Natural Language Processing (NLP) have achieve...
We propose a new approach to the Chinese word segmentation problem that
...