Explore the intersection of AI and healthcare in this 51-minute podcast episode featuring Eric Landry, CTO/CAIO at Zeteo Health. Delve into crucial topics such as patient engagement through chatbots, medical data management, and the challenges of implementing AI in healthcare. Learn about benchmarking and mitigating hallucinations in language models, addressing privacy concerns, and data localization. Gain insights from Landry's hands-on approach to developing AI solutions and navigating healthcare innovation complexities. Discover the potential of AI in proactively engaging patients and improving health outcomes, while understanding the necessary constraints in the field. Benefit from Landry's extensive experience in machine learning engineering and AI-based solutions, backed by his academic background and industry leadership.
AI in Healthcare - Integrating AI Solutions for Patient Engagement and Data Management
Overview
Syllabus
[] Eric's preferred coffee
[] Takeaways
[] Please like, share, leave a review, and subscribe to our MLOps channels!
[] ML and AI in 2005
[] Last job at Babylon Health
[] Data access solutions
[] Prioritize AI ML Team Success
[] Eric's current work
[] Engage in holistic help
[] High-stakes chatbots
[] Navigating Communication Across Diverse Communities
[] When Bots Go Wrong
[] Health care challenges ahead
[] Behavioral health tech challenges
[] Stress from Apps Notifications
[] Combining different guardrails tools
[] Navigating Privacy AI
[] Wrap up
Taught by
MLOps.community
Related Courses
-
Extending AI: From Industry to Innovation
-
AI Agents for Consumers - The Future of AI and Consumer Empowerment
-
Data Governance and AI - Challenges and Opportunities in MLOps
-
How to Systematically Test and Evaluate LLM Apps - MLOps Podcast
-
Micro Graph Transformer - Powering Small Language Models for Data Product Ecosystems
