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AI-powered products are changing healthcare delivery by enabling more personalized, effective, and efficient care at scale.
However, deploying these systems in a highly regulated industry presents unique challenges in ensuring consistency, safety, and reliability.
In this talk, we will walk through Sword Health’s journey developing and launching Phoenix by sharing practical strategies to deliver impactful patient-centric solutions that enhance care. We’ll explore learnings in building effective guardrails, implementing robust evaluation frameworks, choosing the right architecture and optimization approach, collecting user feedback and maintaining data and evaluation-driven development practices.
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.
