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A Conceptual Framework to Predict Disease Progressions in Patients with Chronic Kidney Disease, Using Machine
Nichalini Kandasamy1, Thierry Chaussalet1, Artie Basukoski1
1School of Computer Science & Engineering, University of Westminster, London, UK.
Studies in Health Technology and Informatics
|June 30, 2023
Summary
This study introduces a framework combining Process Mining and Machine Learning for healthcare. This integration aims to enhance the analysis of healthcare processes using advanced data science techniques.
Area of Science:
- Data Science
- Artificial Intelligence
- Healthcare Informatics
Background:
- Process Mining and Machine Learning are established techniques with separate applications in healthcare.
- The combined use of Process Mining and Machine Learning in healthcare is an emerging research area.
- Existing literature extensively covers individual applications but lacks integrated frameworks.
Purpose of the Study:
- To propose a feasible framework for the simultaneous application of Process Mining and Machine Learning in healthcare.
- To explore the synergistic potential of integrating these two powerful analytical techniques.
- To advance the data-driven analysis of healthcare processes.
Main Methods:
- Development of a novel framework integrating Process Mining and Machine Learning algorithms.
- Utilizing process logs and patient data for analysis.
- Applying machine learning models to insights derived from process mining.
Main Results:
- The proposed framework demonstrates the feasibility of combining Process Mining and Machine Learning.
- Potential for enhanced understanding and optimization of healthcare workflows.
- Identified opportunities for improved patient care and operational efficiency.
Conclusions:
- The integration of Process Mining and Machine Learning offers significant advantages for healthcare analytics.
- The proposed framework provides a foundation for future research and practical implementation.
- This combined approach can lead to more intelligent and efficient healthcare systems.
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