Brunel University Research Archive(BURA) preserves and enables easy and open access to all
types of digital content. It showcases Brunel's research outputs.
Research contained within BURA is open access, although some publications may be subject
to publisher imposed embargoes. All awarded PhD theses are also archived on BURA.
Browsing by Author Naseem, U
Showing results 1 to 8 of 8
| Issue Date | Title | Author(s) |
| 21-Apr-2022 | Benchmarking for biomedical natural language processing tasks with a domain specific ALBERT | Naseem, U; Dunn, AG; Khushi, M; Kim, J |
| 26-May-2022 | Benchmarking for Public Health Surveillance tasks on Social Media with a Domain-Specific Pretrained Language Model | Naseem, U; Lee, B; Khushi, M; Kim, J; Dunn, AG |
| 16-Jul-2021 | BioALBERT: A Simple and Effective Pre-trained Language Model for Biomedical Named Entity Recognition | Naseem, U; Khushi, M; Reddy, V; Rajendran, S; Razzak, I; Kim, J |
| 18-Jul-2021 | Classifying vaccine sentiment tweets by modelling domain-specific representation and commonsense knowledge into context-aware attentive GRU | Naseem, U; Khushi, M; Kim, J; Dunn, A |
| 15-Mar-2021 | A comparative analysis of active learning for biomedical text mining | Naseem, U; Khushi, M; Khan, SK; Shaukat, K; Moni, MA |
| 11-Jul-2023 | K-PathVQA: Knowledge-Aware Multimodal Representation for Pathology Visual Question Answering | Naseem, U; Khushi, M; Dunn, AG; Kim, J |
| 17-Feb-2021 | Text mining of stocktwits data for predicting stock prices | Jaggi, M; Mandal, P; Narang, S; Naseem, U; Khushi, M |
| 31-Mar-2022 | Vision-Language Transformer for Interpretable Pathology Visual Question Answering | Naseem, U; Khushi, M; Kim, J |
