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AI in Healthcare // Eric Landry // #249

Jul 19, 2024
51:05
Snipd AI
Seasoned AI and Machine Learning leader, Eric Landry, discusses AI in healthcare, focusing on patient engagement through chatbots, managing medical data, benchmarking LLMs, limiting hallucinations, privacy concerns, and data localization. He emphasizes the potential for AI to engage patients proactively and improve health outcomes despite necessary constraints in healthcare innovation.
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Podcast summary created with Snipd AI

Quick takeaways

  • Eric Landry emphasizes AI's potential for proactive patient engagement in healthcare.
  • Managing medical data in AI involves addressing privacy concerns and data localization.

Deep dives

Challenges of AI in Healthcare in 2005

Entering the field of AI in 2005 posed challenges due to computational constraints, as detailed in a thesis on document clustering. Working with Java algorithms and limited resources made data processing, transformation, and cleaning daunting tasks. The progression to better computational resources facilitated faster algorithm iteration and experimentation, highlighting the significant advancements in technology.

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