Bring heart assessmentcloser to home.

AI-assisted assessment of cardiac function from echocardiography video, through a smartphone—supporting clinicians in their decisions.

Illustration of a healthcare professional using a smartphone to record an echocardiography image on an ultrasound monitor
AI-generated illustration of the intended workflow

Existing equipment.More information for care.

Many healthcare facilities have ultrasound equipment but limited access to specialists. EasyEF aims to turn images from existing equipment into additional information for care teams.

  1. Capture the video

    Trained healthcare professionals use a smartphone to record the echocardiography image on an ultrasound monitor.

  2. Get an AI-assisted assessment

    Cloud-based AI assesses left ventricular contraction from the video and returns the result through the app.

  3. Support clinical decisions

    Clinicians consider the result alongside symptoms and other clinical information to guide further assessment and referral priorities.

A better chance for concerns to be recognised.

Closer to patients

Aiming to make initial assessment more accessible at local healthcare facilities.

More information for care teams

Supporting clinicians as they consider who may need further evaluation.

Connected care

Potential to support referral priorities and resource use within a prepared healthcare system.

These are intended impacts. Available evidence does not yet establish lives saved or a reduction in mortality.

Evidence to inform the next step.

218

Participants in the test

93.6%

Overall accuracy in the test

A test at Rayong Hospital, December 2025–January 2026

Included 76 pre-chemotherapy assessments and 142 left ventricular function assessments, with results confirmed by a cardiologist.

Results varied by cardiac function group. Further evaluation across hospitals is needed.

Reported results by group

Reported groupReported correct classification
poor LV100%
good LV96.9%
fair LV27.3%

The lower result in the fair LV group highlights an area for further development. These findings apply to this participant group and do not establish performance in every setting.

What comes next

The project plans to evaluate use in at least five hospitals, alongside platform development, user acceptance, and readiness as medical device software.

Source: EasyEF Lunch Symposium CNF 17th, 26 March 2026, pp. 55–59.

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