1 code implementation • 9 Feb 2023 • Omid Rohanian, Mohammadmahdi Nouriborji, Hannah Jauncey, Samaneh Kouchaki, ISARIC Clinical Characterisation Group, Lei Clifton, Laura Merson, David A. Clifton
To our knowledge, this is the first comprehensive study specifically focused on creating efficient and compact transformers for clinical NLP tasks.
1 code implementation • 17 Oct 2022 • Omid Rohanian, Hannah Jauncey, Mohammadmahdi Nouriborji, Bronner P. Gonçalves, Christiana Kartsonaki, ISARIC Clinical Characterisation Group, Laura Merson, David Clifton
Processing information locked within clinical health records is a challenging task that remains an active area of research in biomedical NLP.
1 code implementation • 12 Oct 2022 • Mohammadmahdi Nouriborji, Omid Rohanian, Samaneh Kouchaki, David A. Clifton
Different strategies have been proposed in the literature to alleviate these problems, with the aim to create effective compact models that nearly match the performance of their bloated counterparts with negligible performance losses.
1 code implementation • 7 Sep 2022 • Omid Rohanian, Mohammadmahdi Nouriborji, Samaneh Kouchaki, David A. Clifton
Language models pre-trained on biomedical corpora, such as BioBERT, have recently shown promising results on downstream biomedical tasks.
Ranked #2 on Named Entity Recognition (NER) on BC2GM
1 code implementation • SemEval (NAACL) 2022 • Mohammadmahdi Nouriborji, Omid Rohanian, David Clifton
This paper outlines the system using which team Nowruz participated in SemEval 2022 Task 7 Identifying Plausible Clarifications of Implicit and Underspecified Phrases for both subtasks A and B.