# Analyzing Medical Data with Process Mining: a COVID-19 Case Study

arXiv: https://arxiv.org/abs/2202.04625 · HTML: https://mlsanity.com/paper/2202.04625/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 12 references that are in the map.
- First posted on arXiv 8 Feb 2022.

## Built on by (most cited first, 3 of 3)

- [Explainable Artificial Intelligence for Improved Modeling of Processes](https://mlsanity.com/paper/2212.00695/) (2022)
- [Process Modeling and Conformance Checking in Healthcare: A COVID-19 Case Study](https://mlsanity.com/paper/2209.10897/) (2022)
- [Process-Aware Analysis of Treatment Paths in Heart Failure Patients: A Case Study](https://mlsanity.com/paper/2403.10544/) (2024)

## Abstract (arXiv)

The recent increase in the availability of medical data, possible through automation and digitization of medical equipment, has enabled more accurate and complete analysis on patients' medical data through many branches of data science. In particular, medical records that include timestamps showing the history of a patient have enabled the representation of medical information as sequences of events, effectively allowing to perform process mining analyses. In this paper, we will present some preliminary findings obtained with established process mining techniques in regard of the medical data of patients of the Uniklinik Aachen hospital affected by the recent epidemic of COVID-19. We show that process mining techniques are able to reconstruct a model of the ICU treatments for COVID patients.