AI Medical Compendium Journal:
International journal of population data science

Showing 1 to 4 of 4 articles

I-SIRch: AI-powered concept annotation tool for equitable extraction and analysis of safety insights from maternity investigations.

International journal of population data science
BACKGROUND: Maternity care is a complex system involving treatments and interactions between patients, healthcare providers, and the care environment. To enhance patient safety and outcomes, it is crucial to understand the human factors (e.g. individ...

Machine learning models in trusted research environments - understanding operational risks.

International journal of population data science
INTRODUCTION: Trusted research environments (TREs) provide secure access to very sensitive data for research. All TREs operate manual checks on outputs to ensure there is no residual disclosure risk. Machine learning (ML) models require very large am...

De-identification of free text data containing personal health information: a scoping review of reviews.

International journal of population data science
INTRODUCTION: Using data in research often requires that the data first be de-identified, particularly in the case of health data, which often include Personal Identifiable Information (PII) and/or Personal Health Identifying Information (PHII). Ther...

Quantifying depression-related language on social media during the COVID-19 pandemic.

International journal of population data science
INTRODUCTION: The COVID-19 pandemic had clear impacts on mental health. Social media presents an opportunity for assessing mental health at the population level.