Work

Heterogeneous Graph Embeddings of Electronic Health Records Improve Critical Care Disease Predictions

Year: 2020

Type: conference-paper

Source: Lecture notes in computer science

DOI: 10.1007/978-3-030-59137-3_2

Authors: Tingyi Wanyan, Martin Kang, Marcus A. Badgeley, Kipp W. Johnson, Jessica K. De Freitas, Fayzan F. Chaudhry, Akhil Vaid, Shan Zhao, Riccardo Miotto, Girish N. Nadkarni, Fei Wang, Justin Rousseau, Ariful Azad, Ying Ding, Benjamin S. Glicksberg

Institutions: Cornell University, Indiana University Bloomington, Weill Cornell Medicine, Indiana University, The University of Texas at Austin, Icahn School of Medicine at Mount Sinai, Mayo Clinic, Nference (United States), Massachusetts General Hospital, Massachusetts Institute of Technology

Language: English

Topic: Machine Learning in Healthcare

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: closed

OpenAlex ID: W3088312795

FWCI: 0.382

Cites: 13

Cited by: 7

Related to: 10