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explICU: A web-based visualization and predictive modeling toolkit for mortality in intensive care patients.

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    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |January 7, 2016
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    Summary

    explICU is a web service designed to aid in preventing intensive care unit (ICU) mortality by visualizing patient electronic health records (EHRs) and performing predictive modeling. This tool simplifies risk factor identification for better patient outcomes.

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    Area of Science:

    • Medical Informatics
    • Clinical Data Analytics
    • Predictive Modeling in Healthcare

    Background:

    • Preventing mortality in intensive care units (ICUs) is a critical healthcare priority.
    • Electronic Health Records (EHRs) provide a rich data source for predictive modeling of patient mortality.
    • Visualizing patient event timelines is crucial for identifying mortality risk factors in ICUs.

    Purpose of the Study:

    • To develop a user-friendly web service, explICU, for analyzing ICU patient data.
    • To integrate EHR data hosting, event timeline visualization, and predictive modeling capabilities.
    • To simplify the process of identifying patient risk factors for mortality.

    Main Methods:

    • Hosting Electronic Health Records (EHR) data within a web service.
    • Developing interactive visualizations for patient event timelines based on user preferences.
    • Implementing backend predictive modeling for mortality risk assessment.
    • Presenting analytical results through intuitive, interactive visualizations.

    Main Results:

    • A novel web service, explICU, has been developed to streamline ICU data analysis.
    • The service facilitates visualization of patient event timelines and predictive modeling.
    • It aims to reduce the time and technical expertise required for identifying mortality risk factors.

    Conclusions:

    • explICU offers an accessible platform for healthcare professionals to leverage EHR data for mortality prediction.
    • The integration of visualization and predictive modeling enhances the identification of critical patient trends.
    • This approach supports proactive interventions to prevent ICU mortality.