The biomedical literature is growing rapidly, and the extraction of meaningful information
from the large amount of literature is increasingly important. Biomedical named entity …

Abstract Named Entity Recognition is the process of identifying different entities in a given
context. Biomedical Named Entity Recognition (BNER) is the task of extracting chemical …

Many approaches have been tried for the classification of arrhythmia. Due to the dynamic
nature of electrocardiogram (ECG) signals, it is challenging to use traditional handcrafted …

Aiming at the problems of Chinese named entity recognition in the field of apple diseases
and pests, including various entities categories, entities with aliases or abbreviations, and …

Background Automatic and accurate recognition of various biomedical named entities from
literature is an important task of biomedical text mining, which is the foundation of extracting …

Hazard and operability analysis (HAZOP) is one of the most commonly used hazard analysis
methods in the petrochemical industry. The large amount of unstructured data in HAZOP …

In the field of agricultural pests and diseases, there is a lack of annotated data and standard
word formations, so standard Named entity recognition (NER) technology is not effective …

Automatic recognizing mutation mentions plays a fundamental and critical role in extracting
variant-disease relation from biomedical literature. In this paper, we proposed an advanced …

Conventional machine learning approaches adopted for large-scale social media analysis
have encountered significant limitations in capturing the underlying dynamics, evolution …

Objective: To design and implement a simple and highly integrated primer design software
for detection of highly variable bacteria. Methods: Firstly, gene named entity recognition …