Michael S Pulia
Biographic Data
| ID | 5545227 |
|---|---|
| NAME | Michael S Pulia |
| GIVEN NAMES | Michael S |
| FAMILY NAME | Pulia |
| SIGNATURE | PULIA M S |
| AFFILIATIONS | BerbeeWalsh Department of Emergency Medicine, University of Wisconsin School of Medicine and Public Health |
| ORCID | 0000-0001-5809-4060 |
| VERIFIED | Yes |
| TOTAL WORKS | 1 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 1 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2019 |
| H-INDEX | 0 |
Training and Interpreting Machine Learning Algorithms to Evaluate Fall Risk After Emergency Department Visits
BACKGROUND: 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. Here we examine the potential utility of automated risk stratification and referral intervention to screen older adults for fall risk after emergency department (ED) visits. OBJECTIVE: This study evaluated several machine learning methodol…
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Training and Interpreting Machine Learning Algorithms to Evaluate Fall Risk After Emergency Department Visits
BACKGROUND: 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. Here we examine the potential utility of automated risk stratification and referral intervention to screen older adults for fall risk after emergency department (ED) visits. OBJECTIVE: This study evaluated several machine learning methodol…
AdaBoost (1 work) · Algorithm (1 work) · Artificial Intelligence (1 work) · Artificial Intelligence (1 work) · Balance, Gait, and Falls Prevention (1 work) · Computer Science (1 work) · Confidence interval (1 work) · Context (archaeology) (1 work) · Emergency and Acute Care Studies (1 work) · Emergency department (1 work)