3 citations · 3 across the 2 of their papers we have counts for
5 papers · 1 filter
Improved Biomedical Word Embeddings in the Transformer Era
Jiho Noh, Ramakanth Kavuluru
Biomedical word embeddings are usually pre-trained on free text corpora with neural methods that capture local and global distributional properties. They are leveraged in downstrea…
Attention-Gated Graph Convolutions for Extracting Drug Interaction Information from Drug Labels
Tung Tran, Ramakanth Kavuluru, Halil Kilicoglu
Preventable adverse events as a result of medical errors present a growing concern in the healthcare system. As drug-drug interactions (DDIs) may lead to preventable adverse events…
A Multi-Task Learning Framework for Extracting Drugs and Their Interactions from Drug Labels
Tung Tran, Ramakanth Kavuluru, Halil Kilicoglu
Preventable adverse drug reactions as a result of medical errors present a growing concern in modern medicine. As drug-drug interactions (DDIs) may cause adverse reactions, being a…
Neural Metric Learning for Fast End-to-End Relation Extraction
Tung Tran, Ramakanth Kavuluru
Relation extraction (RE) is an indispensable information extraction task in several disciplines. RE models typically assume that named entity recognition (NER) is already performed…
Chemical-protein relation extraction with ensembles of SVM, CNN, and RNN models
Yifan Peng, Anthony Rios, Ramakanth Kavuluru +1
Text mining the relations between chemicals and proteins is an increasingly important task. The CHEMPROT track at BioCreative VI aims to promote the development and evaluation of s…