Episode 2 · Brazil

Practical solutions to health data poverty

Prof. Alexandre Chiavegatto Filho · Associate Professor of Machine Learning in Healthcare, University of São Paulo

Mar 2024 · 31MIN 18SEC

Listen on your preferred channel

Practical solutions to health data poverty

Listen

About this episode

How a team in Brazil is maximising the impact of data-driven technology for underserved communities - and what the global community can learn from Brazil's approach to data diversity.

Health Data AI Implementation Global South

“The world is becoming more like Brazil.”
Prof. Alexandre Chiavegatto Filho

What we cover

01Global lessons from local successes: how Brazil's diverse datasets serve as a model for the world
02Overcoming data challenges and algorithm performance limitations in rural settings
03Neonatal mortality prediction using routinely collected data
04Ensuring that those from whom data is collected see direct benefits from its use
05Balancing highly tuned local solutions with scalable models for broader contexts
06ITU/WHO focus group on AI for health: benchmarking model performance across LMIC settings
07Using transfer learning to enhance model performance and local impact
08Prof. Filho's recommendations for innovators and implementers in the EU, US, and UK

About the guest

Prof. Alexandre Chiavegatto Filho

Associate Professor of Machine Learning in Healthcare, University of São Paulo

Alexandre Chiavegatto Filho is an Associate Professor of Machine Learning in Healthcare at the Department of Epidemiology, School of Public Health, University of São Paulo. He directs the Laboratory of Big Data and Predictive Analysis in Health (Labdaps), which includes a team of 30 researchers focused on developing AI algorithms to improve healthcare decisions.

Transcript

Working in digital health?

Heard something relevant to your work?

Shubs consults on clinical leadership, evidence strategy, and digital health market access. If this conversation sparked something, it is worth a conversation.

Shubs takes on consulting work with startups, investors, and global organisations across digital health.

Working on something in digital health?

→ Get in touch

Send to a friend

How to develop AI that addresses health inequities

Joe Alderman · NHS Anaesthetist and NIHR Clinical Lecturer in AI, University of Birmingham

Joe Alderman has a rare double view: anaesthetist by night, AI academic by day. His insights on what it takes to deploy and monitor AI in healthcare - with a lens on not leaving people behind - are relevant wherever in the world you are. We cover health data poverty, the STANDING Together initiative, algorithmic bias, LLM safety for patients and clinicians, anti-patterns in the industry, and what people building in low-resource settings specifically need to think about.

→ Listen

#10B·

Feb 2025

Ethics for digital health companies

Jess Morley · Digital Ethics Center, Yale University

A special bonus episode: a focused cut of the conversation with Jess Morley on making ethics a real business priority for digital health companies - not a nice-to-have. How do you stop your ethical initiative from getting kicked down the roadmap when good intentions meet business realities?