Potentially inappropriate polypharmacy is an important predictor of 30-day emergency hospitalisation in older adults: a machine learning feature validation study.
Journal:
Age and ageing
Published Date:
May 31, 2025
Abstract
BACKGROUND: Machine learning (ML) models in healthcare are crucial for predicting clinical outcomes, and their effectiveness can be significantly enhanced through improvements in accuracy, generalisability, and interpretability. To achieve widespread adoption in clinical practice, risk factors identified by these models must be validated in diverse populations.
Authors
Keywords
Age Factors
Aged
Aged, 80 and over
Emergency Service, Hospital
Female
Geriatric Assessment
Hospitalization
Humans
Inappropriate Prescribing
Machine Learning
Male
Polypharmacy
Potentially Inappropriate Medication List
Reproducibility of Results
Risk Assessment
Risk Factors
Time Factors
United Kingdom