12 citations · 24 across the 5 of their papers we have counts for
5 papers
AD-BERT: Using Pre-trained contextualized embeddings to Predict the Progression from Mild Cognitive Impairment to Alzheimer's Disease
Chengsheng Mao, Jie Xu, Luke Rasmussen +9
Objective: We develop a deep learning framework based on the pre-trained Bidirectional Encoder Representations from Transformers (BERT) model using unstructured clinical notes from…
Natural language processing to identify lupus nephritis phenotype in electronic health records
Yu Deng, Jennifer A. Pacheco, Anh Chung +14
Systemic lupus erythematosus (SLE) is a rare autoimmune disorder characterized by an unpredictable course of flares and remission with diverse manifestations. Lupus nephritis, one…
Evaluating the Portability of an NLP System for Processing Echocardiograms: A Retrospective, Multi-site Observational Study
Prakash Adekkanattu, Guoqian Jiang, Yuan Luo +14
While natural language processing (NLP) of unstructured clinical narratives holds the potential for patient care and clinical research, portability of NLP approaches across multipl…
Identifying Sub-Phenotypes of Acute Kidney Injury using Structured and Unstructured Electronic Health Record Data with Memory Networks
Zhenxing Xu, Jingyuan Chou, Xi Sheryl Zhang +10
Acute Kidney Injury (AKI) is a common clinical syndrome characterized by the rapid loss of kidney excretory function, which aggravates the clinical severity of other diseases in a…
Characterizing Design Patterns of EHR-Driven Phenotype Extraction Algorithms
Yizhen Zhong, Luke Rasmussen, Yu Deng +10
The automatic development of phenotype algorithms from Electronic Health Record data with machine learning (ML) techniques is of great interest given the current practice is very t…