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A pipeline for tabular dataset formation from unstructured data provided by ACR Appropriateness Criteria guidelines

Eduardo, A.; Loureiro, R. M.; Tachibana, A.; Netto, P.; Almeida, T. F. d.; Monteiro, L. H. A.; Santos, A. P. d.

2022-04-21 health informatics
10.1101/2022.04.20.22274096 medRxiv
Show abstract

Currently, data performns a critical concept for disparate human activities, from law to technology. Among data-centric technologies, clinical decision support systems (CDSS) figures out as one of the most promising for healthcare. Despite the technological advances facilitating its implementation, the maintainance of knowledge base for CDSS remains open to improvements. Here, we argue that the Appropriateness Criteria provided by ACR guidelines can be used as a open data-source that, combined with appropriate algorithms, can push forward basic research and technological developments regarding knowledge base for CDSS. Therefore, we developed a pipeline capable of forming tabular datasets from ACR guidelines, stored in a web site as textual PDF files. We also experimentally demonstrate that the proposed pipeline successfully recorvers the interested contents, and the best composition, in terms of its component algorithms, is discussed. Future research focused on algorithms flexibility in the face of PDF template updates could improve our work.

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