Interoperable Voice AI for Healthcare: From Speech to Clinical Intelligence
Details
Healthcare conversations contain a wealth of valuable clinical information, but much of it remains locked in unstructured speech. Turning these conversations into standardised, actionable healthcare data is a significant challenge—and an important opportunity for AI.
In this session, we’ll explore an end-to-end approach to building voice-enabled AI applications for healthcare, covering how clinical conversations can be transformed from speech into structured data and subsequently used to power downstream AI/ML applications.
### What we'll explore
- 🎙️ Voice AI & Speech Processing — Converting real-world clinical conversations into usable digital information
- 🏥 Healthcare Interoperability — Structuring clinical information to support interoperability and downstream healthcare workflows
- 🧠 Clinical NLP & Intelligence — Extracting meaningful clinical insights from unstructured conversations
- ⚡ Event-Driven Architecture — Designing scalable pipelines for processing and acting on healthcare data
- 🔐 Security & Privacy — Key considerations for handling sensitive healthcare information
- ☁️ Scalable AI Applications — Architectural considerations for building production-ready AI systems in regulated healthcare environments
The session will provide a practical perspective on the intersection of Voice AI, healthcare data, interoperability, NLP, and cloud-native AI/ML architectures.
Whether you're working in AI/ML, healthcare technology, cloud architecture, software engineering, or simply interested in the future of voice-enabled healthcare, this session will offer valuable insights into how these technologies can come together to build intelligent and scalable healthcare applications.
Join us to explore how we can move from speech → structured healthcare data → clinical intelligence.