AIMC Topic: Accountable Care Organizations

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Comparison of Machine Learning Algorithms Identifying Children at Increased Risk of Out-of-Home Placement: Development and Practical Considerations.

Health services research Mar 6, 2025
OBJECTIVE: To develop a machine learning (ML) algorithm capable of identifying children at risk of out-of-home placement among a Medicaid-insured population.
Humans Machine Learning Algorithms Retrospective Studies Female Male Risk Assessment Infant Adolescent Child, Preschool Child ROC Curve Logistic Models United States Foster Home Care Medicaid Ohio Accountable Care Organizations
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A deep learning model for pediatric patient risk stratification.

The American journal of managed care Oct 1, 2019
OBJECTIVES: Current models for patient risk prediction rely on practitioner expertise and domain knowledge. This study presents a deep learning model-a type of machine learning that does not require human inputs-to analyze complex clinical and financ...
Humans Neural Networks, Computer Prospective Studies Reproducibility of Results Risk Factors Health Resources Risk Assessment Deep Learning Child Socioeconomic Factors Residence Characteristics Age Factors Health Services Sex Factors Accountable Care Organizations
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