Benchmarking Predictive Models in Electronic Health Records: Sepsis Length of Stay Prediction

Belal Alsinglawi, Fady Alnajjar, Omar Mubin, Mauricio Novoa, Ola Karajeh, Omar Darwish

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Forecasting Sepsis length of stay is a challenge for hospitals worldwide. Although there are many attempts to improve sepsis length of stay prediction; however, there is still lack of baselining prediction metrics that can give better results for sepsis length of stay prediction in management hospital systems. This paper introduces a research architecture to predict and benchmark the Length of Stay (LOS) for Sepsis diagnoses from electronic medical records using the machine learning models. The architecture considered the time factor to identify the outperforming algorithms for Sepsis LOS prediction. This work contributes to the field of predictive modelling and information visualization for hospital management systems. Our results showed that the ensemble methods in particular the random forest (RF) outdo other classification models to predict the LOS for Sepsis from electronic medical records for Intensive Care Unit “ICU”-based hospitalizations.

Original languageEnglish
Title of host publicationAdvanced Information Networking and Applications - Proceedings of the 34th International Conference on Advanced Information Networking and Applications, AINA 2020
EditorsLeonard Barolli, Flora Amato, Francesco Moscato, Tomoya Enokido, Makoto Takizawa
PublisherSpringer
Pages258-267
Number of pages10
ISBN (Print)9783030440404
DOIs
Publication statusPublished - 2020
Event34th International Conference on Advanced Information Networking and Applications, AINA 2020 - Caserta, Italy
Duration: Apr 15 2020Apr 17 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1151 AISC
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference34th International Conference on Advanced Information Networking and Applications, AINA 2020
Country/TerritoryItaly
CityCaserta
Period4/15/204/17/20

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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