9 citations · 14 across the 8 of their papers we have counts for
8 papers
Harnessing Large Language Models for Biomedical Named Entity Recognition
Jian Chen, Leilei Su, Cong Sun
Background and Objective: Biomedical Named Entity Recognition (BioNER) is a foundational task in medical informatics, crucial for downstream applications like drug discovery and cl…
Extracting Post-Acute Sequelae of SARS-CoV-2 Infection Symptoms from Clinical Notes via Hybrid Natural Language Processing
Zilong Bai, Zihan Xu, Cong Sun +13
Accurately and efficiently diagnosing Post-Acute Sequelae of COVID-19 (PASC) remains challenging due to its myriad symptoms that evolve over long- and variable-time intervals. To a…
Generative Large Language Models Trained for Detecting Errors in Radiology Reports
Cong Sun, Kurt Teichman, Yiliang Zhou +8
In this retrospective study, a dataset was constructed with two parts. The first part included 1,656 synthetic chest radiology reports generated by GPT-4 using specified prompts, w…
A Framework for Human Evaluation of Large Language Models in Healthcare Derived from Literature Review
Thomas Yu Chow Tam, Sonish Sivarajkumar, Sumit Kapoor +12
With generative artificial intelligence (AI), particularly large language models (LLMs), continuing to make inroads in healthcare, it is critical to supplement traditional automate…
Deep learning with noisy labels in medical prediction problems: a scoping review
Yishu Wei, Yu Deng, Cong Sun +3
Objectives: Medical research faces substantial challenges from noisy labels attributed to factors like inter-expert variability and machine-extracted labels. Despite this, the adop…
Demonstration-based learning for few-shot biomedical named entity recognition under machine reading comprehension
Leilei Su, Jian Chen, Yifan Peng +1
Although deep learning techniques have shown significant achievements, they frequently depend on extensive amounts of hand-labeled data and tend to perform inadequately in few-shot…
Biomedical named entity recognition using BERT in the machine reading comprehension framework
Cong Sun, Zhihao Yang, Lei Wang +3
Recognition of biomedical entities from literature is a challenging research focus, which is the foundation for extracting a large amount of biomedical knowledge existing in unstru…
Chemical-protein Interaction Extraction via Gaussian Probability Distribution and External Biomedical Knowledge
Cong Sun, Zhihao Yang, Leilei Su +4
Motivation: The biomedical literature contains a wealth of chemical-protein interactions (CPIs). Automatically extracting CPIs described in biomedical literature is essential for d…