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Are Some AI-Driven Diagnostics Innovations Ethnically and Racially Biased?
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digital health maven dot edu – episode 3: November 14, 2018
This episode focuses on the emerging world of digital diagnostics. Innovations in this growing sub-sector of the digital health industry use data, software and devices to hopefully improve the detection and diagnosis of cancer, depression, malaria and other conditions.
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You’ll learn about five key market challenges associated with digital diagnostics, including data diversity (click the image below for an overview of the five challenges discussed in this episode). One key question some are asking is this: are some AI-driven diagnostic solutions ethnically and racially biased?
What does this mean? Well, there are concerns that data sets being used to train digital diagnostic models (for machine and deep learning) are not diverse enough to ensure high accuracy across a range of populations.
This is especially important in the area of skin cancer where not having data about how it presents in dark skinned individuals could make these diagnostic tools not only inaccurate, but potentially life threatening.
The digital health maven dot edu podcast is designed to deepen your understanding (and ability to leverage) trends, technologies and innovations that are re-shaping global health.
The podcast showcases excerpts from lectures featuring unique digital health market intelligence developed by Fard and other experts related to artificial intelligence, mobile health, voice technologies, Big Data and other fast-moving innovations.
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About the Host: This podcast is hosted by Fard Johnmar, digital health futurist, researcher, speaker and helper. Learn more about Fard and his work by clicking here.
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