Papers by Ali Amin-Nejad

1 papers
Exploring Transformer Text Generation for Medical Dataset Augmentation (2020.lrec-1)

Copied to clipboard

Challenge: Natural Language Processing (NLP) is a powerful tool to unlock the vast troves of unstructured data in clinical text.
Approach: They propose a method for augmenting unstructured patient information to allow NLP model development on downstream clinically relevant tasks.
Outcome: The proposed method beats baselines on a downstream classification task and can be used for NLP model development.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations