Bailey Taylor
Dados Biográficos
| ID | 5516564 |
|---|---|
| NOME | Bailey Taylor |
| PRENOMES | Bailey |
| SOBRENOME | Taylor |
| ASSINATURA | TAYLOR B |
| AFILIAÇÕES | Tulane University |
| VERIFICADO | Não |
| TOTAL DE OBRAS | 2 |
| TOTAL DE CITAÇÕES | 0 |
| TOTAL COMO AUTOR | 2 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2025 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2026 |
| ÍNDICE H | 0 |
Leveraging machine learning algorithms and explainable AI for predicting mental health disorder treatment at the workplace
Mental health disorders in the workplace pose a significant global public health challenge, often resulting in reduced productivity. Timely and accurate prediction is essential for facilitating early and effective interventions. In this study, we evaluated six machine learning (ML) algorithms namely logistic regression, random forest, gradient boosting (GB), categorical boosting (CB), support vector machine, and neural network for their ability t…
Food Insecurity, Neighborhood Disorder, and Homelessness among People with Serious Mental Illness
The health effects of social conditions such as income, education, and employment have been demonstrated to be persistent and wide-reaching. In this study, we examine the effect of social determinants of health, those conditions in which people live, among individuals with serious mental illnesses (SMI) who are actively engaged with mental health services. Using a sample of 203 clients at a community mental health clinic, this study (1) explores …
Sem obras proeminentes nesta página.
Food Insecurity, Neighborhood Disorder, and Homelessness among People with Serious Mental Illness
The health effects of social conditions such as income, education, and employment have been demonstrated to be persistent and wide-reaching. In this study, we examine the effect of social determinants of health, those conditions in which people live, among individuals with serious mental illnesses (SMI) who are actively engaged with mental health services. Using a sample of 203 clients at a community mental health clinic, this study (1) explores …
Leveraging machine learning algorithms and explainable AI for predicting mental health disorder treatment at the workplace
Mental health disorders in the workplace pose a significant global public health challenge, often resulting in reduced productivity. Timely and accurate prediction is essential for facilitating early and effective interventions. In this study, we evaluated six machine learning (ML) algorithms namely logistic regression, random forest, gradient boosting (GB), categorical boosting (CB), support vector machine, and neural network for their ability t…
Mental health (2 obras) · Occupational safety and health (2 obras) · Suicide prevention (2 obras) · Digital Mental Health Interventions (1 obras) · Employment and Welfare Studies (1 obras) · Explainable Artificial Intelligence (XAI (1 obras) · Food insecurity (1 obras) · Food Security and Health in Diverse Populations (1 obras) · Homelessness and Social Issues (1 obras) · Human Factors and Ergonomics (1 obras)