Detection of Temporal Clinical Events in Non-Temporal, Non-Annotated Data

Findings substantiate the assumption that, in a structured process-based domain (e.g., clinical care) if an attribute is strongly associated with another one, but not the other way around, this could imply temporality.

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Publication Details

Journal
Studies in health technology and informatics
Published
2025-04-08
DOI
https://doi.org/10.3233/shti250038
Primary Topic
Data Mining Algorithms and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Detection of Temporal Clinical Events in Non-Temporal, Non-Annotated Data

Dimitrios Zikos, Philip Eappen, Ryan N. Schmidt
Studies in health technology and informatics
Data Mining Algorithms and Applications
article

Detection of Temporal Clinical Events in Non-Temporal, Non-Annotated Data

Dimitrios Zikos, Philip Eappen, Ryan N. Schmidt
article en

Abstract

Findings substantiate the assumption that, in a structured process-based domain (e.g., clinical care) if an attribute is strongly associated with another one, but not the other way around, this could imply temporality.

Studies in health technology and informaticsVol. 323
Cape Breton University (CA), Texas Tech University (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 82%
Data Mining Algorithms and Applications
DOIOpen Access PDFOpenAlex
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Detection of Temporal Clinical Events in Non-Temporal, Non-Annotated Data — Dimitrios Zikos, Philip Eappen, et al. · Studies in health technology and informatics (2025) | TGRS Research Map | TGRS