Name
Leveraging AI to overcome data disparities in women's health
Date & Time
Thursday, May 30, 2024, 1:00 PM - 1:45 PM
Description

Powered by Intelligent Health Association

 

In an era where artificial intelligence is poised to revolutionize every aspect of healthcare, the persistent data disparities in women's health present both a formidable challenge and a unique opportunity for innovation. "Bridging the Gap: Empowering Women's Health through AI Innovation" is a groundbreaking panel discussion that aims to catalyze change in this critical area. Led by Susan Sly, a respected leader in artificial intelligence, the panel aims to highlight the glaring disparities in the data for women’s health.

Despite women making up approximately 50% of the global population, they are significantly underrepresented in clinical research, leading to a dearth of data that affects the accuracy and effectiveness of medical treatments and AI algorithms. For instance, women account for only 34% of participants in clinical trials across the spectrum of disease areas, a disparity that has profound implications for understanding and treating conditions that disproportionately affect women. Moreover, diseases such as cardiovascular conditions, which are the leading cause of death for women globally, are often misdiagnosed due to gender-specific symptoms that are not adequately represented in current data models.

This panel will address critical questions such as:

  • How can AI be leveraged to fill the data gaps in women’s health, particularly in areas like menopause and cardiovascular disease?
  • What are the ethical considerations in deploying AI technologies to ensure they do not perpetuate existing biases?
  • How can the healthcare industry foster innovation in AI that is inclusive and representative of women's health needs?

People attending this panel will gain invaluable insights into the latest advancements in AI that are specifically aimed at enhancing women’s health outcomes. Moreover, they will be equipped with knowledge on how to apply these innovations in clinical practice, ensuring that their female patients receive the most accurate diagnoses and effective treatments. This panel is not just a conversation; it's a call to action for all stakeholders in the healthcare ecosystem to prioritize and address the critical issue of data disparities in women's health through the power of AI.

Session Type
Panel