Improving Prediction Models’ Propriety in Intensive-Care Unit, by Enforcing an Advance Notice Period

Tomer Hermelin, Pierre Singer, Nadav Rappoport

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

Abstract

Intensive-Care-Units (ICUs) are time-critical, and sufficient reaction time is crucial. Previous studies of systems for alerting life-threatening events in the ICU, suffer from “immediate” events bias. In this research, we present a new approach for outcome prediction in ICU admissions, which takes into consideration the constraint of an advance notice of a predicted outcome. We showcase the approach over mortality and sepsis-3 predictions and compare it to existing approaches. We’ve created a set of Neural Network models that implement and evaluate the existing and the suggested approaches using the MIMIC-III data. We show that the performance is affected significantly when enforcing a notice period for mortality prediction, but not affected for sepsis-3 prediction. Further, we examine whether models need to be trained for a specific notice period, or whether the approach could be incorporated at the evaluation level. We found that adding notice enforcement post-model training, has no significant performance loss compared to incorporating the notice period during training, within the bounds of the trained lookahead. The concept of adding Alert-Interval could be applied to other clinical scenarios, where having advance notice is essential.

Original languageEnglish
Title of host publicationArtificial Intelligence in Medicine - 20th International Conference on Artificial Intelligence in Medicine, AIME 2022, Proceedings
EditorsMartin Michalowski, Syed Sibte Raza Abidi, Samina Abidi
PublisherSpringer Science and Business Media Deutschland GmbH
Pages167-177
Number of pages11
ISBN (Electronic)978-031-09342-5
ISBN (Print)978-3-031-09341-8
DOIs
StatePublished - 2022
Event20th International Conference on Artificial Intelligence in Medicine, AIME 2022 - Halifax, Canada
Duration: 14 Jun 202217 Jun 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13263 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Artificial Intelligence in Medicine, AIME 2022
Country/TerritoryCanada
CityHalifax
Period14/06/2217/06/22

Keywords

  • Intensive care units
  • Deep learning
  • Forecasting
  • Electronic health records

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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