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DSxHE: Building a world where data improves everyone's health (Virtual)

Thu, 23 Nov

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Online Conference

Join us to launch our new strategy and welcome Angela Saini for a discussion on 'Why do we categorise patients?'

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DSxHE: Building a world where data improves everyone's health (Virtual)
DSxHE: Building a world where data improves everyone's health (Virtual)

Time & Location

23 Nov 2023, 18:30 – 20:30

Online Conference

About the event

The Data Science for Health Equity (DSxHE) community is hosting an event to launch our 3-year strategy, laying out DSxHE’s focus areas for 2024–2027.

Our primary objective is to bring together researchers, healthcare professionals, and policymakers to help bring the latest data-driven innovations into practice in order to better understand and ultimately reduce health inequalities. We are delighted to welcome Angela Saini (MIT) as our keynote speaker. 

Please note that this event will be hybrid, combining both in-person and virtual participation. As in-person attendance is limited, we kindly ask that you only register for an in-person ticket if you are certain you can attend in person.

If you would like to attend the launch event in person, please use the registration link provided here.

If you wish to attend online, please RSVP on this event.

Please direct any enquiries to Maddy Howell (info.dsxhe@gmail.com).

This event is supported by the Turing Health Equity interest group and The Health Foundation.

Strategy Launch Schedule (subject to change)

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       Time                                           Session

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18:35 - 18:45  ------------  An overview of DSxHE's three-year strategy

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18:45 - 19:20  -------------  Roundtable discussions: how should we define and apply concepts like fairness, justice, ethics & trust?

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19:20 - 20:00  --------------   Keynote speaker: Angela Saini (in conversation hosted by Maxine Mackintosh)

Title: Why do we categorise patients?

Outline: Medicine has long sifted people into groups for the purposes of treatment and diagnosis. But where do our categories come from, and what purpose do they really serve? At a time when medical researchers are rethinking the use of race and gender labels, how can data scientists map human variation in a more useful way, one which genuinely improves the health outcomes of marginalised and disadvantaged individuals?

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20:00 - 20:05 --------------   Open mic

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Keynote speaker

Angela Saini teaches science writing at MIT and her writing has appeared in National Geographic, Wired, and Foreign Policy. She is the author of four books, including Superior: The Return of Race Science, which was a finalist for the LA Times Book Prize and Inferior: How Science Got Women Wrong, which has been translated into fourteen languages. Her latest book, The Patriarchs, was a finalist for the Orwell Prize. Angela has a Masters in Engineering from the University of Oxford.

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