Ensuring fairness and inclusion in AI-guided patient screening

by Mehdi Juma

The current pandemic has laid bare the inequalities in access to services and the impact this has on health and social outcomes for marginalised segments of society.

This is not a new issue . What is new, is the richness of the data to provide insights into the inequalities and their underlying causes, at least in countries where this data is collected to a high-level of accuracy such as in the UK and within the NHS and social care.

Using large, connected data sources, applying AI technology now allows services to actively identify and reduce social inequalities in both access and outcomes.

Here, researcher and HN Data Scientist, Sara Reis considers how machine-learning approaches and data can be used to identify those most in need of care but are often under-served.

Read Sara’s paper.