Morning tea with IHealthE

Artificial intelligence (AI) and machine learning (ML) are increasingly central to driving future healthcare innovation. However, the data collected in biomedical and healthcare research is often “dirty”—sourced from multiple systems with inconsistent or absent standardisation.

In this seminar, attendees joined two of Tyree IHealthE’s leaders for an insightful discussion on the challenges of preparing data for AI and ML applications. The conversation explored the extensive effort biomedical scientists and engineers invest in cleaning, annotating, harmonising, and curating datasets—tasks that are both time-consuming and prone to human error.

The session addressed the critical question: How can we transform dirty data to support the future of healthcare innovation? Participants gained valuable perspectives on the importance of data quality and the strategies needed to unlock the full potential of AI in healthcare.