most citedBidirectional LSTM-CRF for Clinical Concept Extraction

47 citations · 87 across the 4 of their papers we have counts for

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cs.CL2024

Improving Vietnamese-English Medical Machine Translation

Nhu Vo, Dat Quoc Nguyen, Dung D. Le +2

Machine translation for Vietnamese-English in the medical domain is still an under-explored research area. In this paper, we introduce MedEV -- a high-quality Vietnamese-English pa…

cs.CL2024

SumTra: A Differentiable Pipeline for Few-Shot Cross-Lingual Summarization

Jacob Parnell, Inigo Jauregi Unanue, Massimo Piccardi

Cross-lingual summarization (XLS) generates summaries in a language different from that of the input documents (e.g., English to Spanish), allowing speakers of the target language…

cs.CL2024

A Generative Adversarial Attack for Multilingual Text Classifiers

Tom Roth, Inigo Jauregi Unanue, Alsharif Abuadbba +1

Current adversarial attack algorithms, where an adversary changes a text to fool a victim model, have been repeatedly shown to be effective against text classifiers. These attacks,…

cs.CL20232 cited

T3L: Translate-and-Test Transfer Learning for Cross-Lingual Text Classification

Inigo Jauregi Unanue, Gholamreza Haffari, Massimo Piccardi

Cross-lingual text classification leverages text classifiers trained in a high-resource language to perform text classification in other languages with no or minimal fine-tuning (z…

cs.CL201647 cited

Bidirectional LSTM-CRF for Clinical Concept Extraction

Raghavendra Chalapathy, Ehsan Zare Borzeshi, Massimo Piccardi

Extraction of concepts present in patient clinical records is an essential step in clinical research. The 2010 i2b2/VA Workshop on Natural Language Processing Challenges for clinic…

cs.CL2016

An Investigation of Recurrent Neural Architectures for Drug Name Recognition

Raghavendra Chalapathy, Ehsan Zare Borzeshi, Massimo Piccardi

Drug name recognition (DNR) is an essential step in the Pharmacovigilance (PV) pipeline. DNR aims to find drug name mentions in unstructured biomedical texts and classify them into…