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Health equity = 𝒇(data)

What?

Data science for global health

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We use informatics and data science to create implementable digital health tools designed to provably improve healthcare in resource-limited settings

Why?

Equitable accuracy

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When populations are under-represented in predictive tools, they risk disproportionate exposure to inaccuracy. We collect high-quality data on neglected populations and health concerns to concentrate accuracy where it is needed most.

How?

Capacity building through & during research

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We integrate training and capacity building into our projects to have a direct and provable impact on patient outcomes during and through research

See our
[academic exchange program] and [hospital renovation project]

Where?

Global Lab for Global Impact

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LiGHT is an international  lab hosted at

Yale School of Medicine [@BIDS] 
&

Swiss Federal Insitute of Technology (EPFL) School of Computer Science [@MLO]

 

Who?

Global Academic-NGO Network 

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We work with collaborators across Sub-Saharan Africa and several international NGOs to ensure needs-based, implementable technology and fair data ownership.

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