253 citations
- National Institutes of HealthUS28 papers
- National Institutes of Health Clinical CenterUS4 papers
- Howard UniversityUS3 papers
- University of FribourgCH3 papers
- Yale UniversityUS3 papers
- National Eye InstituteUS2 papers
- University of Maryland, College ParkUS2 papers
- A. Alikhanyan National LaboratoryAM1 paper
- Arizona State UniversityUS1 paper
- Children's Hospital of PhiladelphiaUS1 paper
- Cornell UniversityUS1 paper
- Duke-NUS Medical SchoolSG1 paper
6 papers · 1 filter
Leveraging Professional Radiologists' Expertise to Enhance LLMs' Evaluation for Radiology Reports
Qingqing Zhu, Xiuying Chen, Qiao Jin +6
In radiology, Artificial Intelligence (AI) has significantly advanced report generation, but automatic evaluation of these AI-produced reports remains challenging. Current metrics,…
Quality of Answers of Generative Large Language Models vs Peer Patients for Interpreting Lab Test Results for Lay Patients: Evaluation Study
Zhe He, Balu Bhasuran, Qiao Jin +6
Lab results are often confusing and hard to understand. Large language models (LLMs) such as ChatGPT have opened a promising avenue for patients to get their questions answered. We…
Bioformer: an efficient transformer language model for biomedical text mining
Li Fang, Qingyu Chen, Chih-Hsuan Wei +2
Pretrained language models such as Bidirectional Encoder Representations from Transformers (BERT) have achieved state-of-the-art performance in natural language processing (NLP) ta…
BERT-GT: Cross-sentence n-ary relation extraction with BERT and Graph Transformer
Po-Ting Lai, Zhiyong Lu
A biomedical relation statement is commonly expressed in multiple sentences and consists of many concepts, including gene, disease, chemical, and mutation. To automatically extract…
A self-attention based deep learning method for lesion attribute detection from CT reports
Yifan Peng, Ke Yan, Veit Sandfort +2
In radiology, radiologists not only detect lesions from the medical image, but also describe them with various attributes such as their type, location, size, shape, and intensity.…
NegBio: a high-performance tool for negation and uncertainty detection in radiology reports
Yifan Peng, Xiaosong Wang, Le Lu +3
Negative and uncertain medical findings are frequent in radiology reports, but discriminating them from positive findings remains challenging for information extraction. Here, we p…