no code implementations • 12 Sep 2023 • Ramya Tekumalla, Juan M. Banda
The COVID-19 pandemic has presented significant challenges to the healthcare industry and society as a whole.
no code implementations • 10 Sep 2022 • Ramya Tekumalla, Juan M. Banda
Supervised learning algorithms are heavily reliant on annotated datasets to train machine learning models.
no code implementations • 11 Jul 2022 • Ramya Tekumalla, Juan M. Banda
Social media is often utilized as a lifeline for communication during natural disasters.
no code implementations • EMNLP (NLP-COVID19) 2020 • Ramya Tekumalla, Juan M. Banda
Since the classification of COVID-19 as a global pandemic, there have been many attempts to treat and contain the virus.
1 code implementation • 7 Apr 2020 • Juan M. Banda, Ramya Tekumalla, Guanyu Wang, Jingyuan Yu, Tuo Liu, Yuning Ding, Katya Artemova, Elena Tutubalina, Gerardo Chowell
As the COVID-19 pandemic continues its march around the world, an unprecedented amount of open data is being generated for genetics and epidemiological research.
1 code implementation • 31 Mar 2020 • Ramya Tekumalla, Juan M. Banda
There has been a dramatic increase in the popularity of utilizing social media data for research purposes within the biomedical community.
no code implementations • 31 Mar 2020 • Ramya Tekumalla, Juan M. Banda
With the increase in popularity of deep learning models for natural language processing (NLP) tasks, in the field of Pharmacovigilance, more specifically for the identification of Adverse Drug Reactions (ADRs), there is an inherent need for large-scale social-media datasets aimed at such tasks.