Deep representation learning of patient data from Electronic Health Records (EHR): A systematic review
Year: 2020
Type: review
Study design: Systematic Review
Authors: Yuqi Si, Jingcheng Du, Zhao Li, Xiaoqian Jiang, Timothy Miller, Fei Wang, W. Jim Zheng, Kirk Roberts
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
Funders: National Science Foundation, Cancer Prevention and Research Institute of Texas, Patient-Centered Outcomes Research Institute, National Institutes of Health, National Institute of General Medical Sciences, U.S. National Library of Medicine, National Center for Advancing Translational Sciences
Awards: G1234997963, G2029016872, G287445649, Data Science and Informatics Core for Cancer Research, G3575224597, G3641532177, CAREER: Interpretable Deep Modeling of Discrete Time Event Sequences, G4073300813, G4113126293, Recruitment of Rising Stars, Open Health Natural Language Processing Collaboratory, G486457145, G4972693717, Decentralized differentially-private methods for dynamic data release and analysis, G5534231150, G5883340063, G6515066292, G7048620842, G7757262149, G822719969, G8998506876, G9000020272, G9000105665, G9000134663, G9000241611, G957413421, G95928508
OpenAlex ID: W3092301826