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CHPC - Research Computing and Data Support for the University

In addition to deploying and operating high performance computational resources and providing advanced user support and training, CHPC serves as an expert team to broadly support the increasingly diverse research computing needs on campus. These needs include support for big data, big data movement, data analytics, security, virtual machines, Windows science application servers, protected environments for data mining and analysis of protected health information, and advanced networking. Visit our Getting Started page for more information.

 Why the existing rule systems don't work as well

A generic rule-based pipeline for patient cohort identification

By Jianlin Shi1, Jianyin Shao1, Kevin Graves1, Celena Peters1, Kelly Peterson2, John F Hurdle1

1Department of Biomedical Informatics, 2Division of Epidemiology, University of Utah

Our aim is a one-for-all pipeline based on a use-friendly rule design app. We identify the patient cohort with high risk of heart disease for clinical trial from clinical notes with 13 heterogeneous selection criteria.

Our pipeline is demonstrated to be effective and suitable for rapid development of patient cohort identification solutions.

For more information about algorithms, see a related article in the Journal of Biomedical Informatics.

System Status

General Environment

last update: 2022-05-22 14:23:04
General Nodes
system cores % util.
kingspeak 816/832 98.08%
notchpeak 1824/3212 56.79%
lonepeak 2008/2620 76.64%
Owner/Restricted Nodes
system cores % util.
ash 808/4092 19.75%
notchpeak 12091/12228 98.88%
kingspeak 5553/5576 99.59%
lonepeak 416/416 100%

Protected Environment

last update: 2022-05-22 14:20:03
General Nodes
system cores % util.
redwood 636/716 88.83%
Owner/Restricted Nodes
system cores % util.
redwood 4201/4824 87.09%

Cluster Utilization

Last Updated: 5/20/22