A study of generalizability of recurrent neural network-based predictive models for heart failure onset risk using a large and heterogeneous EHR data set. - Laila Rasmy; Yonghui Wu; Ningtao Wang; Xin Geng; W. Jim Zheng; Fei Wang 001; Hulin Wu; Hua Xu 001; Degui Zhi (J. Biomed. Informatics, 2018)

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)

Med-BERT: pre-trained contextualized embeddings on large-scale structured electronic health records for disease prediction. - Laila Rasmy; Yang Xiang 003; Ziqian Xie; Cui Tao; Degui Zhi (CoRR, 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)

AQUA: an Advanced QUery Architecture for the SPARC Portal. - Niloofar Shahidi; Xuanzhi Lin; Yuda Munarko; Laila Rasmy; Tram Ngo (F1000Research, 2021)

Med-BERT: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction. - Laila Rasmy; Yang Xiang 003; Ziqian Xie; Cui Tao; Degui Zhi (npj Digit. Medicine, 2021)

Automatic Sub-Pixel Co-Registration of Remote Sensing Images Using Phase Correlation and Harris Detector. - Laila Rasmy; Imane Sebari; Mohamed Ettarid (Remote. Sens., 2021)

Pancreatic cancer risk prediction using recurrent neural network models trained on electronic health records and claims data. - Laila Rasmy; Peter Beshara; Bijun S. Kannadath; Degui Zhi (AMIA, 2022)

Explainability versus Accuracy to Engender Trust. - Angela Ross; Laila Rasmy; Degui Zhi; Kathleen McGrow (AMIA, 2022)

PK-RNN-V E: A deep learning model approach to vancomycin therapeutic drug monitoring using electronic health record data. - Masayuki Nigo; Hong Thoai Nga Tran; Ziqian Xie; Han Feng; Bingyu Mao; Laila Rasmy; Hongyu Miao 001; Degui Zhi (J. Biomed. Informatics, 2022)

A Deep-Learning-based Two-Compartment Predictive Model (PKRNN-2CM) for Vancomycin Therapeutic Drug Monitoring. - Bingyu Mao; Ziqian Xie; Laila Rasmy; Masayuki Nigo; Degui Zhi (ICHI, 2023)

Training Recurrent Neural Network-Based Model to Predict COVID-19 Patient Risk for PASC using Pytorch_EHR - Hands-on Tutorial on N3C. - Laila Rasmy; Ziqian Xie; Degui Zhi (ICHI, 2023)

PheME: A deep ensemble framework for improving phenotype prediction from multi-modal data. - Shenghan Zhang; Haoxuan Li; Ruixiang Tang; Sirui Ding; Laila Rasmy; Degui Zhi; Na Zou 001; Xia Hu 001 (ICHI, 2023)

Prompting Large Language Models for Clinical Temporal Relation Extraction. - Jianping He 002; Laila Rasmy; Haifang Li; Jianfu Li; Zenan Sun; Evan Yu; Degui Zhi; Cui Tao (CoRR, 2024)

Advancing Pancreatic Cancer Prediction with a Next Visit Token Prediction Head on top of Med-BERT. - Jianping He 002; Laila Rasmy; Degui Zhi; Cui Tao (CoRR, 2025)