Abstract
This talk provides valuable insights into Sword Health's real-world experience implementing AI in healthcare, focusing on practical strategies for developing consistent, safe and reliable AI-powered healthcare solutions. Through a case study format, attendees will learn concrete approaches to building guardrails, evaluation frameworks, and data-driven development practices. The session will be valuable for those looking to understand the challenges of deploying AI systems in real-world settings.
Interview:
What is the focus of your work?
Building and scaling machine learning systems that support Sword Health's goal of reinventing how patients access and receive care, by creating a more human, more clinically effective, and more scalable way to treat patients.
What’s the motivation for your talk?
I look forward to sharing our practical learnings because, while many discuss AI's potential in healthcare, few are openly sharing strategies for responsible implementation.
Who is your talk for?
The session will be valuable for those looking to understand the challenges of deploying AI systems in real-world settings.
What do you want someone to walk away with from your presentation?
This talk provides valuable insights into Sword Health's real-world experience implementing AI in healthcare, focusing on practical strategies for developing consistent, safe and reliable AI-powered healthcare solutions. Through a case study format, attendees will learn concrete approaches to building guardrails, evaluation frameworks, and data-driven development practices.
What do you think is the next big disruption in software?
How Generative AI will change how we work everyday.
Speaker
Clara Matos
Director of Applied AI @Sword Health, Focused on Building and Scaling Machine Learning Systems
Clara enjoys working in the intersection of Machine Learning, Product, and Engineering, solving problems in a pragmatic and iterative way. She currently leads Applied AI at Sword Health, where her team is reinventing how patients access and receive care, by creating a more human, more clinically effective, and more scalable way to treat patients. She is focused on building and scaling machine learning systems that help achieve Sword's mission of freeing 2 million people from pain.