Comprehend Medical is a stateless and Health Insurance Portability and Accountability Act
(HIPAA) eligible Named Entity Recognition (NER) and Relationship Extraction (RE) service …

The China Conference on Knowledge Graph and Semantic Computing (CCKS) 2020
Evaluation Task 3 presented clinical named entity recognition and event extraction for the …

Named entity recognition (NER) is a widely applicable natural language processing task
and building block of question answering, topic modeling, information retrieval, etc. In the …

With the advent of Web 2.0, there exist many online platforms that result in massive textual-
data production. With ever-increasing textual data at hand, it is of immense importance to …

Background Finding biomedical named entities is one of the most essential tasks in
biomedical text mining. Recently, deep learning-based approaches have been applied to …

Background Despite significant advancements in biomedical named entity recognition
methods, the clinical application of these systems continues to face many challenges:(1) …

The number of scientific publications in the literature is steadily growing, containing our
knowledge in the biomedical, health, and clinical sciences. Since there is currently no …

As the generation and accumulation of massive electronic health records (EHR), how to
effectively extract the valuable medical information from EHR has been a popular research …

Objective Extracting clinical entities and their attributes is a fundamental task of natural
language processing (NLP) in the medical domain. This task is typically recognized as 2 …

With rapid development of electronic medical records, more and more attention has been
attracted to reuse these data for research and commercial. As the entity recognition is one of …