Supplementary Material - Current Polution Reports

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Summary:

 

Methodology

This section overviews the methodology applied to search and select the literature for the "Unresolved Challenges" section of this review. To ensure a balance between quantitative impact and qualitative relevance, we employed a multi-stage search strategy across two primary scientific databases: PubMed and Web of Science (WoS).

 

We defined the following objectives for our literature search:

  • Identifying innovative integrative frameworks or tools used in this context published predominantly within the past 5 years.
  • Capturing high-impact methodological developments specifically addressing the six core challenges identified in the taxonomy: (1) explainability, (2) longitudinal modeling, (3) missing data, (4) outcome imbalance, (5) causal/mediation analysis, and (6) technical noise.

To perform the searches, terms were grouped into two fundamental categories to ensure the intersection of integration technology and specific methodological hurdles:

  • Category (A) - Core Integration Keywords: "multi-om*", "multimodal data", "multi-view".
  • Category (B) - Methodological Challenge Keywords: "temporal", "longitudinal", "imbalanced", "resampling", "imputation", "missing", "xAI", "explainable", "interpretable", "Trustworthy AI", "batch".

The final queries associated with these databases were constructed using the following logic:

  • $Q_{PubMed}$​: ("multi-om*"[ti] OR "multimodal data"[ti] OR "multi-view"[ti]) AND ("temporal"[ti] OR "longitudinal"[ti] OR "imbalanced"[ti] OR "resampling"[ti] OR "imputation"[ti] OR "missing"[ti] OR "xAI"[ti] OR "explainable"[ti] OR "interpretable"[ti] OR "batch"[ti])
  • $Q_{WoS}$​: TS=("multi-om*" OR "multimodal data" OR "multi-view") AND TS=("temporal" OR "longitudinal" OR "imbalanced" OR "resampling" OR "imputation" OR "missing" OR "xAI" OR "explainable" OR "interpretable" OR "Trustworthy AI" OR "batch")

The final selection of articles was not determined by a single metric but quantitative impact (number of citations, metrics like CNCI), temporal relevance and novelty as well as

Detailed cross-cutting methodological checklist for each framework.

A detailed methodological comparison for each of the idiosyncrasies and challenges of data integration methods by algorithm taxonomic group from studies that work with exposome data is available for download in docx format by clicking this icon Word icon