50 citations · 60 across the 6 of their papers we have counts for
7 papers
Ensuring Safety and Trust: Analyzing the Risks of Large Language Models in Medicine
Yifan Yang, Qiao Jin, Robert Leaman +15
The remarkable capabilities of Large Language Models (LLMs) make them increasingly compelling for adoption in real-world healthcare applications. However, the risks associated with…
AgentMD: Empowering Language Agents for Risk Prediction with Large-Scale Clinical Tool Learning
Qiao Jin, Zhizheng Wang, Yifan Yang +8
Clinical calculators play a vital role in healthcare by offering accurate evidence-based predictions for various purposes such as prognosis. Nevertheless, their widespread utilizat…
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…
Navigating the landscape of COVID-19 research through literature analysis: A bird's eye view
Lana Yeganova, Rezarta Islamaj, Qingyu Chen +8
Timely access to accurate scientific literature in the battle with the ongoing COVID-19 pandemic is critical. This unprecedented public health risk has motivated research towards u…
PDC -- a probabilistic distributional clustering algorithm: a case study on suicide articles in PubMed
Rezarta Islamaj, Lana Yeganova, Won Kim +3
The need to organize a large collection in a manner that facilitates human comprehension is crucial given the ever-increasing volumes of information. In this work, we present PDC (…
Deep learning with sentence embeddings pre-trained on biomedical corpora improves the performance of finding similar sentences in electronic medical records
Qingyu Chen, Jingcheng Du, Sun Kim +2
Capturing sentence semantics plays a vital role in a range of text mining applications. Despite continuous efforts on the development of related datasets and models in the general…
Bridging the Gap: Incorporating a Semantic Similarity Measure for Effectively Mapping PubMed Queries to Documents
Sun Kim, Nicolas Fiorini, W. John Wilbur +1
The main approach of traditional information retrieval (IR) is to examine how many words from a query appear in a document. A drawback of this approach, however, is that it may fai…