186 citations · 261 across the 12 of their papers we have counts for
12 papers
Large Language Models Struggle in Token-Level Clinical Named Entity Recognition
Qiuhao Lu, Rui Li, Andrew Wen +3
Large Language Models (LLMs) have revolutionized various sectors, including healthcare where they are employed in diverse applications. Their utility is particularly significant in…
GRU-D-Weibull: A Novel Real-Time Individualized Endpoint Prediction
Xiaoyang Ruan, Liwei Wang, Charat Thongprayoon +2
Accurate prediction models for individual-level endpoints and time-to-endpoints are crucial in clinical practice. In this study, we propose a novel approach, GRU-D-Weibull, which c…
A Cross-institutional Evaluation on Breast Cancer Phenotyping NLP Algorithms on Electronic Health Records
Sicheng Zhou, Nan Wang, Liwei Wang +4
Objective: The generalizability of clinical large language models is usually ignored during the model development process. This study evaluated the generalizability of BERT-based c…
Discrimination, calibration, and point estimate accuracy of GRU-D-Weibull architecture for real-time individualized endpoint prediction
Xiaoyang Ruan, Liwei Wang, Michelle Mai +3
Real-time individual endpoint prediction has always been a challenging task but of great clinic utility for both patients and healthcare providers. With 6,879 chronic kidney diseas…
An Open Natural Language Processing Development Framework for EHR-based Clinical Research: A case demonstration using the National COVID Cohort Collaborative (N3C)
Sijia Liu, Andrew Wen, Liwei Wang +28
While we pay attention to the latest advances in clinical natural language processing (NLP), we can notice some resistance in the clinical and translational research community to a…
CancerBERT: a BERT model for Extracting Breast Cancer Phenotypes from Electronic Health Records
Sicheng Zhou, Liwei Wang, Nan Wang +2
Accurate extraction of breast cancer patients' phenotypes is important for clinical decision support and clinical research. Current models do not take full advantage of cancer doma…