Time-sensitive clinical concept embeddings learned from large electronic health records. - Yang Xiang 003; Jun Xu 007; Yuqi Si; Zhiheng Li 004; Laila Rasmy; Yujia Zhou 003; Firat Tiryaki; Fang Li 011; Yaoyun Zhang; Yonghui Wu; Xiaoqian Jiang; W. Jim Zheng; et al. (BMC Medical Informatics Decis. Mak., 2019)

Normalizing Clinical Document Titles to LOINC Document Ontology: an Initial Study. - Xu Zuo; Jianfu Li; Bo Zhao 001; Yujia Zhou 003; Xiao Dong; Jon D. Duke; Karthik Natarajan; George Hripcsak; Nigam Shah; Juan M. Banda; Ruth M. Reeves; Hua Xu 001 (AMIA, 2020)

Named Entity Recognition from Table Headers in Randomized Controlled Trial Articles. - Qiang Wei 002; Yujia Zhou 003; Bo Zhao 001; Xinyue Hu 002; Qiaozhu Mei; Cui Tao; Hua Xu 001 (ICHI, 2020)

Representation of EHR data for predictive modeling: a comparison between UMLS and other terminologies. - Laila Rasmy; Firat Tiryaki; Yujia Zhou 003; Yang Xiang 003; Cui Tao; Hua Xu 001; Degui Zhi (J. Am. Medical Informatics Assoc., 2020)

Generalizable Gated Recurrent Neural Network based model to predict COVID-19 patient outcomes on admission. - Laila Rasmy; Bijun S. Kannadath; Masayuki Nigo; Ziqian Xie; Bingyu Mao; Khush A. Patel; Yujia Zhou 003; Xiao Dong; Hua Xu 001; Degui Zhi (AMIA, 2021)

CovRNN: predicting outcomes of COVID-19 patients on admission using their electronic health records with minimal data processing. - Laila Rasmy; Masayuki Nigo; Bijun S. Kannadath; Ziqian Xie; Bingyu Mao; Khush A. Patel; Wanheng Zhang; Yujia Zhou 003; Angela Ross; Hua Xu 001; Degui Zhi (AMIA, 2021)

Simple Recurrent Neural Networks is all we need for clinical events predictions using EHR data. - Laila Rasmy; Jie Zhu; Zhiheng Li 004; Xin Hao; Hong Thoai Tran; Yujia Zhou 003; Firat Tiryaki; Yang Xiang 003; Hua Xu 001; Degui Zhi (CoRR, 2021)

Are synthetic clinical notes useful for real natural language processing tasks: A case study on clinical entity recognition. - Jianfu Li; Yujia Zhou 003; Xiaoqian Jiang; Karthik Natarajan; Serguei V. S. Pakhomov; Hongfang Liu; Hua Xu 001 (J. Am. Medical Informatics Assoc., 2021)

COVID-19 SignSym: a fast adaptation of a general clinical NLP tool to identify and normalize COVID-19 signs and symptoms to OMOP common data model. - Jingqi Wang; Noor Abu-El-Rub; Josh Gray; Huy Anh Pham; Yujia Zhou 003; Frank J. Manion; Mei Liu; Xing Song; Hua Xu 001; Masoud Rouhizadeh; Yaoyun Zhang (J. Am. Medical Informatics Assoc., 2021)

Fast Textual Corpus Retrieval from Electronic Health Records using PDF Parser and TxtSplit Tools. - Yiming Li; Qiang Wei 002; Yujia Zhou 003; Hua Xu 001 (AMIA, 2022)

Zero-shot Clinical Entity Recognition using ChatGPT. - Yan Hu; Iqra Ameer; Xu Zuo; Xueqing Peng; Yujia Zhou 003; Zehan Li; Yiming Li; Jianfu Li; Xiaoqian Jiang; Hua Xu 001 (CoRR, 2023)

Blockchain-enabled immutable, distributed, and highly available clinical research activity logging system for federated COVID-19 data analysis from multiple institutions. - Tsung-Ting Kuo; Anh Pham; Maxim E. Edelson; Jihoon Kim 001; Jason Chan; Yash Gupta; Lucila Ohno-Machado; David M. Anderson; Chandrasekar Balacha; Tyler Bath; Sally L. Baxter; Andrea Becker-Pennrich; et al. (J. Am. Medical Informatics Assoc., 2023)

Information Extraction from Clinical Notes: Are We Ready to Switch to Large Language Models? - Yan Hu; Xu Zuo; Yujia Zhou 003; Xueqing Peng; Jimin Huang; Vipina Kuttichi Keloth; Vincent J. Zhang; Ruey-Ling Weng; Qingyu Chen 001; Xiaoqian Jiang; Kirk E. Roberts; Hua Xu 001 (CoRR, 2024)

CDEMapper: Enhancing NIH Common Data Element Normalization using Large Language Models. - Yan Wang; Jimin Huang; Huan He; Vincent J. Zhang; Yujia Zhou 003; Xubing Hao; Pritham Ram; Lingfei Qian; Qianqian Xie; Ruey-Ling Weng; Fongci Lin; Yan Hu; et al. (CoRR, 2024)

Improving large language models for clinical named entity recognition via prompt engineering. - Yan Hu; Qingyu Chen 001; Jingcheng Du; Xueqing Peng; Vipina Kuttichi Keloth; Xu Zuo; Yujia Zhou 003; Zehan Li; Xiaoqian Jiang; Zhiyong Lu; Kirk Roberts; Hua Xu 001 (J. Am. Medical Informatics Assoc., 2024)

FedFSA: Hybrid and federated framework for functional status ascertainment across institutions. - Sunyang Fu; Heling Jia; Maria Vassilaki; Vipina Kuttichi Keloth; Yifang Dang; Yujia Zhou 003; Muskan Garg; Ronald C. Petersen; Jennifer St Sauver; Sungrim Moon; Liwei Wang 010; Andrew Wen; et al. (J. Biomed. Informatics, 2024)

Developing deep learning-based strategies to predict the risk of hepatocellular carcinoma among patients with nonalcoholic fatty liver disease from electronic health records. - Zhao Li; Lan Lan; Yujia Zhou 003; Ruoxing Li; Kenneth D. Chavin; Hua Xu 001; Liang Li; David J. H. Shih; W. Jim Zheng (J. Biomed. Informatics, 2024)

CDEMapper: enhancing National Institutes of Health common data element use with large language models. - Yan Wang; Jimin Huang; Huan He; Vincent Zhang; Yujia Zhou 003; Xubing Hao; Pritham Ram; Lingfei Qian; Qianqian Xie; Ruey-Ling Weng; Fongci Lin; Yan Hu; et al. (J. Am. Medical Informatics Assoc., 2025)

Social determinants of health extraction from clinical notes across institutions using large language models. - Vipina Kuttichi Keloth; Salih Selek; Qingyu Chen 001; Christopher Gilman; Sunyang Fu; Yifang Dang; Xinghan Chen; Xinyue Hu 002; Yujia Zhou 003; Huan He; Jungwei W. Fan 001; Karen Wang; et al. (npj Digit. Medicine, 2025)