AIMC Topic: Health Services Needs and Demand

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Comparison of methods for tuning machine learning model hyper-parameters: with application to predicting high-need high-cost health care users.

BMC medical research methodology
BACKGROUND: Supervised machine learning is increasingly being used to estimate clinical predictive models. Several supervised machine learning models involve hyper-parameters, whose values must be judiciously specified to ensure adequate predictive p...

Machine learning approach for unmet medical needs among middle-aged adults in South Korea: a cross-sectional study.

BMC health services research
BACKGROUND: South Korea is reported to have higher levels of unmet medical needs (UMN) than other countries, particularly among the middle-aged adult population. Considering that this group constitutes a substantial portion of the country's productiv...

Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To develop a conceptual prediction model framework containing standardized steps and describe the corresponding open-source software developed to consistently implement the framework across computational environments and observational heal...

Factors Associated with HIV Viral Suppression Among Transgender Women in Lima, Peru.

LGBT health
PURPOSE: Globally, transgender women (TGW) experience a high burden of adverse health outcomes, including a high prevalence of HIV and sexually transmitted infections (STIs) as well as psychiatric disorders and substance use disorders. To address gap...