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Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
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A Robust Solution for Real-Time Statistical Analysis of Real-World Data.

Christina Papangelou1, George Karakatsoulis1, Thomas Chatzikonstantinou1

  • 1Institute of Applied Biosciences, Center for Research and Technology Hellas, Thessaloniki, Greece.

Studies in Health Technology and Informatics
|May 17, 2025
PubMed
Summary

Developing a dynamic, scenario-based platform enhances real-time analysis of real-world data (RWD). This approach addresses challenges in transforming RWD into evidence, improving accuracy and speed for complex datasets.

Keywords:
Real-Word DataStandardized FrameworkStatistical Analysis

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Area of Science:

  • Data Science
  • Statistical Analysis
  • Health Informatics

Background:

  • Real-world data (RWD) transformation into evidence faces accuracy and speed challenges.
  • General analysis tools struggle with large, complex datasets and lack adaptability.
  • Standardized, robust methodologies are crucial for real-time data analysis.

Purpose of the Study:

  • Develop a dynamic, scenario-based platform for real-time analysis.
  • Enable correlation and multivariable statistical analysis.
  • Create a versatile platform applicable to multiple use cases.

Main Methods:

  • Platform design emphasizing dynamic and scenario-based functionalities.
  • Implementation of correlation and multivariable statistical analysis modules.
  • Testing across diverse use cases to ensure adaptability.

Main Results:

  • Successful development of a flexible real-time analysis platform.
  • Demonstrated efficiency in handling large and complex datasets.
  • Validation of the platform's applicability in various analytical scenarios.

Conclusions:

  • The developed platform offers a robust solution for real-world data evidence generation.
  • Dynamic, scenario-based analysis improves accuracy and speed.
  • The platform's adaptability supports diverse research and clinical applications.