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The Hidden Bias in Healthcare AI cover
The Hidden Bias in Healthcare AI cover
Into The Metahealth - Web3 & AI in Healthcare

The Hidden Bias in Healthcare AI

The Hidden Bias in Healthcare AI

07min |26/03/2025
Play
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The Hidden Bias in Healthcare AI cover
The Hidden Bias in Healthcare AI cover
Into The Metahealth - Web3 & AI in Healthcare

The Hidden Bias in Healthcare AI

The Hidden Bias in Healthcare AI

07min |26/03/2025
Play

Description

In this episode, we take a critical look at one of the most pressing questions in digital health: Can we truly trust AI in healthcare? With the rapid rise of AI-powered tools promising efficiency and accuracy, it’s easy to overlook a key issue—bias. Drawing from a recent study in npj Digital Medicine, Anca explores how AI systems can unintentionally perpetuate health disparities and what steps we can take to prevent them.


Topics Covered:

  • How bias infiltrates AI systems through data, algorithms, and deployment

  • Real-world consequences of biased AI tools in diagnosis and treatment

  • Examples of disparities in dermatology and risk prediction models

  • Strategies to mitigate bias, including diverse data collection and explainable AI

  • The ethical debate: Can AI help eliminate or worsen existing inequalities in healthcare?


Credits:
Production: MedShake Studio
Host: Anca Petre


Stay connected and learn more:


More about the podcast:
Every week, I dive into the most transformative trends at the intersection of technology and healthcare. From AI-driven breakthroughs in diagnostics to the role of blockchain in securing health data, from decentralized science (DeSci) to NFT-powered health innovation, and from gamified fitness to the potential of digital twins, I’m here to make complex topics simple, accessible, and exciting.


Hosted by Ausha. See ausha.co/privacy-policy for more information.

Description

In this episode, we take a critical look at one of the most pressing questions in digital health: Can we truly trust AI in healthcare? With the rapid rise of AI-powered tools promising efficiency and accuracy, it’s easy to overlook a key issue—bias. Drawing from a recent study in npj Digital Medicine, Anca explores how AI systems can unintentionally perpetuate health disparities and what steps we can take to prevent them.


Topics Covered:

  • How bias infiltrates AI systems through data, algorithms, and deployment

  • Real-world consequences of biased AI tools in diagnosis and treatment

  • Examples of disparities in dermatology and risk prediction models

  • Strategies to mitigate bias, including diverse data collection and explainable AI

  • The ethical debate: Can AI help eliminate or worsen existing inequalities in healthcare?


Credits:
Production: MedShake Studio
Host: Anca Petre


Stay connected and learn more:


More about the podcast:
Every week, I dive into the most transformative trends at the intersection of technology and healthcare. From AI-driven breakthroughs in diagnostics to the role of blockchain in securing health data, from decentralized science (DeSci) to NFT-powered health innovation, and from gamified fitness to the potential of digital twins, I’m here to make complex topics simple, accessible, and exciting.


Hosted by Ausha. See ausha.co/privacy-policy for more information.

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Description

In this episode, we take a critical look at one of the most pressing questions in digital health: Can we truly trust AI in healthcare? With the rapid rise of AI-powered tools promising efficiency and accuracy, it’s easy to overlook a key issue—bias. Drawing from a recent study in npj Digital Medicine, Anca explores how AI systems can unintentionally perpetuate health disparities and what steps we can take to prevent them.


Topics Covered:

  • How bias infiltrates AI systems through data, algorithms, and deployment

  • Real-world consequences of biased AI tools in diagnosis and treatment

  • Examples of disparities in dermatology and risk prediction models

  • Strategies to mitigate bias, including diverse data collection and explainable AI

  • The ethical debate: Can AI help eliminate or worsen existing inequalities in healthcare?


Credits:
Production: MedShake Studio
Host: Anca Petre


Stay connected and learn more:


More about the podcast:
Every week, I dive into the most transformative trends at the intersection of technology and healthcare. From AI-driven breakthroughs in diagnostics to the role of blockchain in securing health data, from decentralized science (DeSci) to NFT-powered health innovation, and from gamified fitness to the potential of digital twins, I’m here to make complex topics simple, accessible, and exciting.


Hosted by Ausha. See ausha.co/privacy-policy for more information.

Description

In this episode, we take a critical look at one of the most pressing questions in digital health: Can we truly trust AI in healthcare? With the rapid rise of AI-powered tools promising efficiency and accuracy, it’s easy to overlook a key issue—bias. Drawing from a recent study in npj Digital Medicine, Anca explores how AI systems can unintentionally perpetuate health disparities and what steps we can take to prevent them.


Topics Covered:

  • How bias infiltrates AI systems through data, algorithms, and deployment

  • Real-world consequences of biased AI tools in diagnosis and treatment

  • Examples of disparities in dermatology and risk prediction models

  • Strategies to mitigate bias, including diverse data collection and explainable AI

  • The ethical debate: Can AI help eliminate or worsen existing inequalities in healthcare?


Credits:
Production: MedShake Studio
Host: Anca Petre


Stay connected and learn more:


More about the podcast:
Every week, I dive into the most transformative trends at the intersection of technology and healthcare. From AI-driven breakthroughs in diagnostics to the role of blockchain in securing health data, from decentralized science (DeSci) to NFT-powered health innovation, and from gamified fitness to the potential of digital twins, I’m here to make complex topics simple, accessible, and exciting.


Hosted by Ausha. See ausha.co/privacy-policy for more information.

Share

Embed

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