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Training and Interpreting Machine Learning Algorithms to Evaluate Fall Risk After Emergency Department Visits

Training and Interpreting Machine Learning Algorithms to Evaluate Fall Risk After Emergency Department Visits

Machine learning is increasingly used for risk stratification in health care. Achieving accurate predictive models do not improve outcomes if they cannot be translated into efficacious intervention. HIP Investigator, Dr. Brian Patterson et al. examined the potential utility of automated risk stratification and referral intervention to screen older adults for fall risk after emergency department visits. This study evaluated several machine learning methodologies for the creation of a risk stratification algorithm using electronic health record data and estimated the effects of a resultant intervention based on algorithm performance in test data.

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