John Pestian
Biographic Data
| ID | 7160404 |
|---|---|
| NAME | John Pestian |
| GIVEN NAMES | John |
| FAMILY NAME | Pestian |
| SIGNATURE | PESTIAN J |
| AFFILIATIONS | Eastern Virginia Medical School |
| ORCID | 0000-0001-5998-249X |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1999 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Using iterative random forest to find geospatial environmental and Sociodemographic predictors of suicide attempts
Taken together, our findings highlight the importance of social determinants and environmental factors in understanding suicide risk among veterans
A Feasibility Study Using a Machine Learning Suicide Risk Prediction Model Based on Open-Ended Interview Language in Adolescent Therapy Sessions
Voice collection technology and associated procedures can be integrated into mental health therapists' workflow. Collected language samples could be classified with good discrimination using machine learning methods
From Research to Community Action: An Assessment of Child and Adolescent Hospitalizations
Population-based data sources describing severe childhood morbidity have been lacking in Virginia. Thus, passage of House Bill 2351 in 1993, which required hospitals to report patient level discharge data, established a mechanism to develop a new population data source. Subsequently, to describe the health status of children, the Virginia Department of Health commissioned a study using these data. The final report, a 189-page document, was distri…
No prominent works on this page.
From Research to Community Action: An Assessment of Child and Adolescent Hospitalizations
Population-based data sources describing severe childhood morbidity have been lacking in Virginia. Thus, passage of House Bill 2351 in 1993, which required hospitals to report patient level discharge data, established a mechanism to develop a new population data source. Subsequently, to describe the health status of children, the Virginia Department of Health commissioned a study using these data. The final report, a 189-page document, was distri…
A Feasibility Study Using a Machine Learning Suicide Risk Prediction Model Based on Open-Ended Interview Language in Adolescent Therapy Sessions
Voice collection technology and associated procedures can be integrated into mental health therapists' workflow. Collected language samples could be classified with good discrimination using machine learning methods
Using iterative random forest to find geospatial environmental and Sociodemographic predictors of suicide attempts
Taken together, our findings highlight the importance of social determinants and environmental factors in understanding suicide risk among veterans
Medicine (3 works) · Psychology (3 works) · Computer Science (2 works) · Environmental health (2 works) · Poison control (2 works) · Suicide and Self-Harm Studies (2 works) · Suicide prevention (2 works) · Action (physics (1 works) · Artificial Intelligence (1 works) · Business (1 works)