A Visualization and Benchmarking Simulator for Clinical Data

Area of Science:

• Medical Informatics
• Big Data Analytics
• Clinical Research Tools

Background:

• Big Data availability is increasing, driving the need for data analysis across industries.
• Medical data, especially from intensive care units (ICUs), is complex and heterogeneous, requiring technical expertise for access and analysis.
• Effective use of ICU patient data is crucial for optimizing treatment and improving patient outcomes.

Purpose of the Study:

• To develop an accessible web application for visualizing and benchmarking the Medical Information Mart for Intensive Care III (MIMIC-III) database.
• To provide clinical staff and researchers with a user-friendly tool for exploring complex patient data.
• To enable the simulation and analysis of disease progression through data individualization.

Main Methods:

• Development of a web-based application with a graphical user interface.
• Integration with the anonymized MIMIC-III database, containing patient demographics, vital signs, and laboratory measurements.
• Implementation of data visualization, benchmarking, and data individualization features for simulation.

Main Results:

• The application offers an easily accessible platform for clinical staff and researchers to interact with MIMIC-III data.
• It serves as a tool for validating anomaly detection algorithms and assessing disease progression.
• Users can modify patient data parameters to simulate various clinical scenarios.

Conclusions:

• The developed web application enhances the accessibility and utility of complex ICU Big Data for clinical and research purposes.
• It supports improved digital decision support systems and clinical process optimization.
• The tool facilitates a deeper understanding of patient data for better healthcare insights and advancements.