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Early Multimodal Data Integration for Data-Driven Medical Research - A Scoping Review.

Julia Gehrmann1, Oya Beyan1,2

  • 1Institute for Biomedical Informatics, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany.

Studies in Health Technology and Informatics
|September 5, 2024
PubMed
Summary

This study reviews early multimodal data integration (MMDI) methods for data-driven medical research (DDMR). It categorizes 21 methods, highlighting characteristics crucial for selecting optimal integration pipelines in complex medical data analysis.

Keywords:
Data-Driven MedicineEarly IntegrationMultimodal Data IntegrationMultimodalityScoping Review

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Area of Science:

  • Medical Informatics
  • Data Science in Healthcare
  • Computational Biology

Background:

  • Data-driven medical research (DDMR) requires multimodal data (MMD) to capture clinical complexity.
  • Early multimodal data integration (MMDI) methods, performed before analysis, range from simple concatenation to deep learning.
  • Late MMDI analyzes modalities separately before combining results.

Purpose of the Study:

  • To systematically review and analyze methods for early multimodal data integration (MMDI).
  • To categorize early MMDI methods and summarize their characteristics for DDMR projects.
  • To inform the selection of optimal MMDI strategies in medical research.

Main Methods:

  • Conducted a scoping review following PRISMA guidelines.
  • Analyzed 21 reviews on early MMDI published between 2019 and 2024.
  • Categorized identified MMDI methods into four distinct groups.

Main Results:

  • Early MMDI methods were classified into four main categories.
  • Key characteristics of each category were summarized to guide method selection.
  • Early MMDI often involves sequential pipeline execution, typically requiring manual optimization.

Conclusions:

  • The choice of early MMDI method depends on research context, data complexity, and team expertise.
  • Future research should compare early vs. late MMDI and automate pipeline optimization.
  • Effective MMDI is essential for holistic DDMR and integrating real-world medical data.