Diagnosing stroke risk in under a minute with AI

1 min read

A major player in the healthtech space asked us to leverage our data capabilities to support improved risk analytics, leading to our investigation of how we could use AI and advanced digital technologies to help doctors easily identify patients at risk of strokes at the point of care and provide guideline-based treatment protocols. We built a mobile-enabled, AI-driven platform that analyses EKG images and identifies stroke risk in under a minute – boosting diagnostic speed and accuracy.

Outcome 1: Reduced diagnoses speed to less than one minute enabled by patient portal
Outcome 2: Established 94% detection rate accuracy
Outcome 3: Prepared platform for FDA approval submission

The challenge

Doctors needed a faster, more accessible way to detect stroke risk – particularly in time-sensitive, point-of-care settings.

The client wanted to create a secure, user-friendly platform that could be used in clinical environments. It needed to deliver results quickly, integrate AI and meet regulatory requirements.

The approach

We developed a cloud-based platform with in-built AI that analyses EKG images captured by mobile devices. The platform includes a clinical guidance tool, leveraging the insights from the EKG to help doctors provide discharged patients automated therapy plans, personalised risk assessments and ensure a safe hand-off to the right long-term care partner.

Impact

With a less than one minute analysis window and 94% detection accuracy, the platform empowers doctors to make faster, evidence-based decisions. It’s also on track for FDA approval – accelerating adoption in real-world clinical settings.

AI & Machine Learning Consulting