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Machine Learning for Asthma Care Continuity by khalyfa07 is a document available to read on EtoBox.
What is Machine Learning for Asthma Care Continuity about?
This study developed a machine learning model to predict the continuity of care (COC) for asthma patients using a dataset of 31,724 adult outpatients from the University of Washington Medicine. The model achieved an accuracy of 88.20% and identified key factors influencing COC, including asthma severity, comorbidities, insurance, and age. The findings suggest that this predictive approach could enhance clinical decision-making and resource allocation in asthma care management.
- Author
- khalyfa07
- Language
- EN