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Towards equitable AI for women’s health: accessible data as a catalyst for innovation

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About this event

What to expect

Explore how accessible, representative health data can make AI for women’s health more equitable in this online expert talk on 29 September 2026.

Hosted by the Turing Clinical AI Interest Group, this one-hour session examines a critical barrier to inclusive healthcare innovation: women have historically been underrepresented in health data. That gap creates significant challenges for researchers and practitioners developing AI systems intended to work fairly across women and diverse populations.

What the talk will cover

Speakers from the AI for Women’s Health Group will explore how improving access to high-quality, representative data can catalyse innovation and support the development of more inclusive AI technologies. The discussion will connect data accessibility with the practical goal of creating healthcare AI that serves a broader range of patients more effectively.

The session features:

  • Dr Bianca Schor, AI Researcher in Women’s Health at Amsterdam UMC
  • Marta Delfino, PhD student at the University of Cambridge

Their talk is supported by a related Nature Women’s Health article, which attendees can read ahead of the session. Together, the presentation and accompanying research offer a focused opportunity to consider how data representation affects the direction, quality and equity of clinical AI.

Who should attend?

This event is designed for people working across healthcare, research, technology and public policy, including:

  • Clinicians interested in the future of AI-enabled healthcare
  • Researchers studying women’s health, health data or clinical AI
  • Data scientists building or evaluating healthcare technologies
  • Policymakers considering fairness, access and representation in AI
  • Anyone interested in more equitable approaches to medical innovation

No specific experience level is stated, making the talk relevant both to specialists and to those looking to understand the core data challenges shaping AI for women’s health.

Event format and registration…

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