Atopic dermatitis or eczema? Consequences of ambiguity in disease name for biomedical literature mining

Abstract

Background Biomedical research increasingly relies on computational approaches to extract relevant information from large corpora of publications. Objective To investigate the consequence of the ambiguity between the use of terms “Eczema” and “Atopic Dermatitis” (AD) from the Information Retrieval perspective, and its impact on meta‐analyses, systematic reviews and text mining. Methods Articles were retrieved by querying the PubMed using terms ‘eczema’ (D003876) and “dermatitis, atopic” (D004485). We used machine learning to investigate the differences between the contexts in which each term is used. We used a decision tree approach and trained model to predict if an article would be indexed with eczema or AD tags. We used text‐mining tools to extract biological entities associated with eczema and AD, and investigated the discrepancy regarding the retrieval of key findings according to the terminology used. Results Atopic dermatitis query yielded more articles related to veterinary science, biochemistry, cellular and molecular biology; the eczema query linked to public health, infectious disease and respiratory system. Medical Subject Headings terms associated with “AD” or “Eczema” differed, with an agreement between the top 40 lists of 52%. The presence of terms related to cellular mechanisms, especially allergies and inflammation, characterized AD literature. The metabolites mentioned more frequently than expected in articles with AD tag differed from those indexed with eczema. Fewer enriched genes were retrieved when using eczema compared to AD query. Conclusions and Clinical Relevance There is a considerable discrepancy when using text mining to extract bio‐entities related to eczema or AD. Our results suggest that any systematic approach (particularly when looking for metabolites or genes related to the condition) should be performed using both terms jointly. We propose to use decision tree learning as a tool to spot and characterize ambiguity, and provide the source code for disambiguation at https://github.com/cfrainay/ResearchCodeBase.

Data‐driven research on eczema: Systematic characterization of the field and recommendations for the future

“…The analysis performed in this study corroborates the discrepancy in the use of AD and eczema terms within the literature that has been highlighted in previous studies 26,44 . Our results point towards a bias in term use depending on the computational method employed; this alludes to the previously articulated notion that AD and eczema terms may be associated to different research communities that have differing views on nomenclature (Appendix S3).…”

“…21 The Bayesian approach allows consistent quantification of uncertainty within parameter estimates and pre- The analysis performed in this study corroborates the discrepancy in the use of AD and eczema terms within the literature that has been highlighted in previous studies. 26,44 Our results point towards a bias in term use depending on the computational method employed;…”

“…A computational tool based on the decision tree to disambiguate AD/eczema‐related queries for both researchers and clinicians has recently been published as an open‐source code, and we highlight its availability. 26 …”

“…It is additionally crucial to keep up to date on literature using both eczema and AD keywords not to miss important findings. A computational tool based on the decision tree to disambiguate AD/eczema‐related queries for both researchers and clinicians has recently been published as an open‐source code, and we highlight its availability 26 …”

“…Also of note, the continued absence of a consensus in nomenclature has resulted in the co‐existence of two main terms for the skin condition, AD and eczema, which have been shown to be linked to different findings and biased to different disciplines. 26 Our study included both AD and eczema terms and retrieved all publications available up to March 2021 without a time constraint, to provide the full picture of the field. Additionally, we included topic modelling to provide a detailed view of the key research topics in the field and methods employed.…”