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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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.
Enhancing Healthcare with Conversational AI
Transitioning from experimentation on algorithm iterations to leveraging conversational design in healthcare, the podcast delves into deploying agnostic AI platforms for cloud-based training. The focus on NLP and AI chatbots, particularly within Babylon Health's conversation platform, showcases the efficacy in deflecting users to automated agents. The importance of meaningful engagements through chatbots to improve healthcare outcomes is emphasized.
Addressing Ethical Challenges in AI-driven Healthcare
Exploring the complex ethical dilemmas in AI-driven healthcare, the podcast discusses the critical need for guardrails and bias detection mechanisms to safeguard patient interactions. The focus on establishing curated knowledge bases and tailored conversational approaches offers insights into enhancing trust and engagement in underserved communities. Understanding the nuances of tone of voice and intent-based responses aims to bridge communication barriers in healthcare conversations.
Implementing Remote Monitoring for Health Engagement
The adoption of wearable devices for remote health monitoring and subsequent integration into conversational AI frameworks reveals promising avenues for real-time health insights. By utilizing these devices to track and notify individuals about health metrics, the podcast highlights the potential to drive proactive healthcare decisions and improve engagement. The emphasis on starting with smaller user groups and incremental scaling underscores the iterative and user-centric approach to healthcare technology implementations.
Eric Landry is a seasoned AI and Machine Learning leader with extensive expertise in software engineering and practical applications in NLP, document classification, and conversational AI. With technical proficiency in Java, Python, and key ML tools, he leads the Expedia Machine Learning Engineering Guild and has spoken at major conferences like Applied Intelligence 2023 and KDD 2020.
AI in Healthcare // MLOps Podcast #249 with Eric Landry, CTO/CAIO @ Zeteo Health.
// Abstract
Eric Landry discusses the integration of AI in healthcare, highlighting use cases like patient engagement through chatbots and managing medical data. He addresses benchmarking and limiting hallucinations in LLMs, emphasizing privacy concerns and data localization. Landry maintains a hands-on approach to developing AI solutions and navigating the complexities of healthcare innovation. Despite necessary constraints, he underscores the potential for AI to proactively engage patients and improve health outcomes.
// Bio
Eric Landry is a technology veteran with 25+ years of experience in the healthcare, travel, and computer industries, specializing in machine learning engineering and AI-based solutions. Holding a Masters in SWE (NLP thesis topic) from the University of Texas at Austin, 2005. He has showcased his expertise and leadership in the field with three US patents, published articles on machine learning engineering, and speaking engagements at the 2023 Applied Intelligence Live, 2020 KDD conference, Data Science Salon 2024, and former leader of Expedia’s MLE guild. Formerly, Eric was the director of AI Engineering and Conversation Platform at Babylon Health and Expedia. Currently CTO/CAIO at Zeteo Health.
// MLOps Jobs board
https://mlops.pallet.xyz/jobs
// MLOps Swag/Merch
https://mlops-community.myshopify.com/
// Related Links
Website: https://www.zeteo.health/
Building Threat Detection Systems: An MLE's Perspective // Jeremy Jordan // MLOps Podcast #134: https://youtu.be/13nOmMJuiAo
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Timestamps:
[00:00] Eric's preferred coffee
[00:16] Takeaways
[01:16] Please like, share, leave a review, and subscribe to our MLOps channels!
[01:32] ML and AI in 2005
[04:43] Last job at Babylon Health
[10:57] Data access solutions
[14:35] Prioritize AI ML Team Success
[16:39] Eric's current work
[20:36] Engage in holistic help
[22:13] High-stakes chatbots
[27:30] Navigating Communication Across Diverse Communities
[31:49] When Bots Go Wrong
[34:15] Health care challenges ahead
[36:05] Behavioral health tech challenges
[39:45] Stress from Apps Notifications
[41:11] Combining different guardrails tools
[47:16] Navigating Privacy AI
[50:12] Wrap up
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