Work

A FHIR-Enabled Streaming Sepsis Prediction System for ICUs

Year: 2018

Type: conference-paper

Source: Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

DOI: 10.1109/embc.2018.8513347

Authors: Joel R. Henry, Dennis Lynch, Jeff Mals, Supreeth P. Shashikumar, Andre Holder, Ashish Sharma, Shamim Nemati

Institutions: Georgia Institute of Technology, Emory University

Language: English

Topic: Sepsis Diagnosis and Treatment

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: closed

Funders: National Institute of General Medical Sciences, National Institute of Environmental Health Sciences, National Center for Advancing Translational Sciences

Awards: Characterizing patients at risk for sepsis through Big Data, Deep Learning and Streaming Analytics for Prediction of Adverse Events in the ICU, G8625582587

OpenAlex ID: W2899236072

FWCI: 10.63

Cites: 4

Cited by: 12

Related to: 10