HyperAIHyperAI

Command Palette

Search for a command to run...

3 months ago

An ensemble CNN method for biomedical entity normalization

{Liang Xu Mengyao Huang Haipeng Chen Pan Deng Xiaowen Ruan}

An ensemble CNN method for biomedical entity normalization

Abstract

Different representations of the same concept could often be seen in scientific reports and publications. Entity normalization (or entity linking) is the task to match the different representations to their standard concepts. In this paper, we present a two-step ensemble CNN method that normalizes microbiology-related entities in free text to concepts in standard dictionaries. The method is capable of linking entities when only a small microbiology-related biomedical corpus is available for training, and achieved reasonable performance in the online test of the BioNLP-OST19 shared task Bacteria Biotope.

Benchmarks

BenchmarkMethodologyMetrics
medical-concept-normalization-on-bb-norm-1PADIA
accuracy: 0.488
wang: 0.684
medical-concept-normalization-on-bb-norm-2PADIA
accuracy: 0.618
wang: 0.758

Build AI with AI

From idea to launch — accelerate your AI development with free AI co-coding, out-of-the-box environment and best price of GPUs.

AI Co-coding
Ready-to-use GPUs
Best Pricing
Get Started

Hyper Newsletters

Subscribe to our latest updates
We will deliver the latest updates of the week to your inbox at nine o'clock every Monday morning
Powered by MailChimp
An ensemble CNN method for biomedical entity normalization | Papers | HyperAI