Temporal electronic phenotyping by mining careflows of breast cancer patients

Arianna Dagliati; L. Sacchi; A. Zambelli; V. Tibollo; L. Pavesi; John H. Holmes; R. Bellazzi

doi:10.1016/j.jbi.2016.12.012

Temporal electronic phenotyping by mining careflows of breast cancer patients

Arianna Dagliati, L. Sacchi, A. Zambelli, V. Tibollo, L. Pavesi, John H. Holmes, R. Bellazzi

Istituti Clinici Scientifici Maugeri Spa – Società Benefit

Research output: Contribution to journal › Article

Abstract

In this work we present a careflow mining approach designed to analyze heterogeneous longitudinal data and to identify phenotypes in a patient cohort. The main idea underlying our approach is to combine methods derived from sequential pattern mining and temporal data mining to derive frequent healthcare histories (careflows) in a population of patients. This approach was applied to an integrated data repository containing clinical and administrative data of more than 4000 breast cancer patients. We used the mined histories to identify sub-cohorts of patients grouped according to healthcare activities pathways, then we characterized these sub-cohorts with clinical data. In this way, we were able to perform temporal electronic phenotyping of electronic health records (EHR) data.

Original language	English
Pages (from-to)	136-147
Number of pages	12
Journal	Journal of Biomedical Informatics
Volume	66
DOIs	https://doi.org/10.1016/j.jbi.2016.12.012
Publication status	Published - Feb 1 2017

Keywords

Careflow mining
Electronic phenotyping
Heterogeneous data sets
Temporal data mining

ASJC Scopus subject areas

Computer Science Applications
Health Informatics

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Dagliati, A., Sacchi, L., Zambelli, A., Tibollo, V., Pavesi, L., Holmes, J. H., & Bellazzi, R. (2017). Temporal electronic phenotyping by mining careflows of breast cancer patients. Journal of Biomedical Informatics, 66, 136-147. https://doi.org/10.1016/j.jbi.2016.12.012

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AU - Holmes, John H.

AU - Bellazzi, R.

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