Development & Deployment of a Real-time Healthcare Predictive Analytics Platform

被引：3

作者：

Boussina, Aaron ^{[1
]}

Shashikumar, Supreeth ^{[1
]}

Amrollahi, Fatemeh ^{[1
]}

Pour, Hayden ^{[1
]}

Hogarth, Michael ^{[1
]}

Nemati, Shamim ^{[1
]}

机构：

[1] Univ Calif San Diego, Div Biomed Informat, San Diego, CA 92093 USA

来源：

2023 45TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY, EMBC | 2023年

关键词：

INTERNATIONAL CONSENSUS DEFINITIONS; SEPTIC SHOCK; SEVERE SEPSIS;

D O I：

10.1109/EMBC40787.2023.10340351

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The deployment of predictive analytic algorithms that can safely and seamlessly integrate into existing healthcare workflows remains a significant challenge. Here, we present a scalable, cloud-based, fault-tolerant platform that is capable of extracting and processing electronic health record (EHR) data for any patient at any time following admission and transferring results back into the EHR. This platform has been successfully deployed within the UC San Diego Health system and utilizes interoperable data standards to enable portability.

引用

页数：4

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