Peter Lubell-Doughtie CTO & Co-Founder Machine Learning for Low Resource Settings How can we turn raw data into measurable improvements in outcomes?

● Improved outcomes ○ Reduce preventable deaths ○ Manage workforce ● Have impact at scale ○ Automation ○ Standards for best practices ○ Reduce time to implementation ○ Reduce time to correction ● Applies to problems we have ○ Find fake and exceptional data ○ Estimate missing data ○ Triage data by risk ○ Predict demand and trends Why Use Machine Learning?

Data management solutions and platforms

Public health and population level interventions

Opportunities ● Significant much room for improvement ● Willingness to experiment Challenges ● Current digital data not collected with ML in mind ● Data sovereignty often requires on-premises deployments Working with governments and NGOs

Opportunities ● Flexibility, sometimes due to lack of pre-existing solutions ● State-of-the-art open source solutions Challenges ● Use ML as a means not an end ● Data consistency across different implementations Scaling Data Management Platforms

Peter Lubell-Doughtie - [email protected] Ephraim Muhia - [email protected] Thank You! [email protected] @peetldee