MoCab: A Model Management System Based on FHIR for Clinical Decision Support

Zhe Ming Kuo, Yi Ju Tseng*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

MoCab is a framework that deploys high-accuracy medical models across various health information systems (HISs) using fast healthcare interoperability resources (FHIR). MoCab simplifies the process by importing and configuring stored models and retrieving data for prediction. Two case studies illustrate how MoCab can be used to support decision-making. The proposed framework increases model reusability across EHRs and improves the clinical decision-making process.

Original languageEnglish
Title of host publicationMEDINFO 2023 - The Future is Accessible
Subtitle of host publicationProceedings of the 19th World Congress on Medical and Health Informatics
EditorsJen Bichel-Findlay, Paula Otero, Philip Scott, Elaine Huesing
PublisherIOS Press BV
Pages1384-1385
Number of pages2
ISBN (Electronic)9781643684567
DOIs
StatePublished - 25 Jan 2024
Event19th World Congress on Medical and Health Informatics, MedInfo 2023 - Sydney, Australia
Duration: 8 Jul 202312 Jul 2023

Publication series

NameStudies in Health Technology and Informatics
Volume310
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Conference

Conference19th World Congress on Medical and Health Informatics, MedInfo 2023
Country/TerritoryAustralia
CitySydney
Period8/07/2312/07/23

Keywords

  • Fast healthcare interoperability resources
  • clinical decision support
  • information management system
  • system design

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