A machine learning approach for identifying predictors of success in a Medicaid-funded, community-based behavioral health program using the Child and Adolescent Needs and Strengths (CANS)-Reference-Cited by-同舟云学术

A machine learning approach for identifying predictors of success in a Medicaid-funded, community-based behavioral health program using the Child and Adolescent Needs and Strengths (CANS)

Published:2021-07 Issue: Volume:126 Page:106010
ISSN:0190-7409
Container-title:Children and Youth Services Review
language:en
Short-container-title:Children and Youth Services Review

Author:

Troy Jesse D.,Torrie Ryan M.,Warner Daniel N.

Publisher

Elsevier BV

Subject

Sociology and Political Science,Developmental and Educational Psychology,Education

Reference27 articles.

1. The Child and Adolescent Needs and Strengths as an Outcome Measure in Community Mental Health: Factor Analysis and a Validation of the Short Form;Alamdari;Community Mental Health Journal,2016

2. The impact of a statewide trauma-informed care initiative in child welfare on the well-being of children and youth with complex trauma;Bartlett;Children and Youth Services Review,2018

3. Predicting outcomes of children in residential treatment: A comparison of a decision support algorithm and a multidisciplinary team decision model;Chor;Children and Youth Services Review,2012

4. Patterns and priorities of service need identified through the Child and Adolescent Needs and Strengths (CANS) assessment;Cordell;Children and Youth Services Review,2016

5. The relationship between precision-recall and ROC curves;Davis;ACM International Conference Proceeding Series,2006

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An Assessment of the Internal Structure of the Child and Adolescent Needs and Strengths (CANS) Using Two Samples of High-Risk Adolescents;Children and Youth Services Review;2024-01

2. Detection of traumatic stress in the presence of traumatic experiences: the role of resilience factors in foster care children five years or younger;International Journal of Mental Health Systems;2023-11-15

3. The application of artificial intelligence in health financing: a scoping review;Cost Effectiveness and Resource Allocation;2023-11-06

4. Detection of complex interpersonal trauma and asset-based resilience factors in foster care youth five years or younger using latent class analysis;2023-01-04

5. Intelligent triage method for early diagnosis autism spectrum disorder (ASD) based on integrated fuzzy multi-criteria decision-making methods;Informatics in Medicine Unlocked;2023