129 citations · 317 across the 23 of their papers we have counts for
39 papers
Comprehensively identifying Long Covid articles with human-in-the-loop machine learning
Robert Leaman, Rezarta Islamaj, Alexis Allot +3
A significant percentage of COVID-19 survivors experience ongoing multisystemic symptoms that often affect daily living, a condition known as Long Covid or post-acute-sequelae of S…
LitCovid in 2022: an information resource for the COVID-19 literature
Qingyu Chen, Alexis Allot, Robert Leaman +5
LitCovid (https://www.ncbi.nlm.nih.gov/research/coronavirus/), first launched in February 2020, is a first-of-its-kind literature hub for tracking up-to-date published research on…
LitMC-BERT: transformer-based multi-label classification of biomedical literature with an application on COVID-19 literature curation
Qingyu Chen, Jingcheng Du, Alexis Allot +1
The rapid growth of biomedical literature poses a significant challenge for curation and interpretation. This has become more evident during the COVID-19 pandemic. LitCovid, a lite…
tmVar 3.0: an improved variant concept recognition and normalization tool
Chih-Hsuan Wei, Alexis Allot, Kevin Riehle +2
Previous studies have shown that automated text-mining tools are becoming increasingly important for successfully unlocking variant information in scientific literature at large sc…
Radiology Text Analysis System (RadText): Architecture and Evaluation
Song Wang, Mingquan Lin, Ying Ding +3
Analyzing radiology reports is a time-consuming and error-prone task, which raises the need for an efficient automated radiology report analysis system to alleviate the workloads o…
A Privacy-Preserving Unsupervised Domain Adaptation Framework for Clinical Text Analysis
Qiyuan An, Ruijiang Li, Lin Gu +5
Unsupervised domain adaptation (UDA) generally aligns the unlabeled target domain data to the distribution of the source domain to mitigate the distribution shift problem. The stan…