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
Head of AI Engineering @Sword Health, Focused on Building and Scaling Machine Learning Systems
Clara currently leads AI Engineering at Sword Health, where she is focused on 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.
Some of the features she has been working on include an AI assistant which supports patients during rehabilitation sessions, a copilot that enhances and scales the Physical Therapist by recommending the best next steps for patient care, automatically filling medical forms based on call transcripts and summarizing key clinical information, among others and a customer support bot available both through chat and phone, which assists patients with all non-clinical tasks.
Find Clara Matos at:
Date
Monday Apr 7 / 10:35AM BST ( 50 minutes )
Location
Windsor (5th Fl.)
Track
Slides
Slides are not available
