Michael D Repplinger
Biographic Data
| ID | 5545228 |
|---|---|
| NAME | Michael D Repplinger |
| GIVEN NAMES | Michael D |
| FAMILY NAME | Repplinger |
| SIGNATURE | REPPLINGER M D |
| AFFILIATIONS | University of Wisconsin–Madison |
| ORCID | 0000-0002-6518-3907 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2017 |
| 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…
Manifestations of HIV stigma and their impact on retention in care for people transitioning from prisons to communities
BACKGROUND: While most people living with HIV who are incarcerated in United States receive appropriate HIV care while they are in prison, interruptions in antiretroviral therapy and virologic failure are extremely common after they are released. The purpose of this study was to describe whether and how HIV stigma influences continuity of care for people living with HIV while they transition from prison to community settings. METHODS: We conducte…
Using database linkages to monitor the continuum of care for hepatitis C virus among syringe exchange clients
No prominent works on this page.
Manifestations of HIV stigma and their impact on retention in care for people transitioning from prisons to communities
BACKGROUND: While most people living with HIV who are incarcerated in United States receive appropriate HIV care while they are in prison, interruptions in antiretroviral therapy and virologic failure are extremely common after they are released. The purpose of this study was to describe whether and how HIV stigma influences continuity of care for people living with HIV while they transition from prison to community settings. METHODS: We conducte…
Using database linkages to monitor the continuum of care for hepatitis C virus among syringe exchange clients
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…
Family medicine (3 works) · Medicine (3 works) · HIV/AIDS Research and Interventions (2 works) · Physical therapy (2 works) · Psychiatry (2 works) · AdaBoost (1 work) · Adolescent Sexual and Reproductive Health (1 work) · Algorithm (1 work) · Artificial Intelligence (1 work) · Artificial Intelligence (1 work)