Cardiology highlights both the promise and limits of AI in clinical practice. The most useful gains often come not just from diagnostics, but from communication and continuity workflows around them.
Where AI helps most
AI can support pattern recognition, risk prioritization, follow-up coordination, and patient communication tied to chronic cardiac care pathways.
Why workflow still matters
Even the best models underperform if results are not routed clearly into care-team workflows and patient follow-up operations.
The practical lesson
The most effective cardiology AI deployments treat diagnostics, outreach, and follow-up as one connected system rather than isolated technology projects.