iHealthScreen Inc. Introduces An Automated Stroke Prediction Model, based on AI and Color Fundus Imaging

iHealthScreen is the First Company to Develop An AI- and Color-Fundus- Image-Based Stroke Prediction model, Funded by the National Institutes of Health (NIH)

iPredict late Stroke prediction model provides a fully automated prediction score for incident stroke and identifies the individuals who are at risk of stroke within 5-years. These results were presented at the international conference: Society for Brain Mapping and Therapeutics World Congress and show that the prediction model may help prevent stroke, saving millions of people from death or disability.

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Once high-resolution images of the patient’s eyes have been captured using a color fundus camera and submitted to the iPredict AI System, the stroke prediction results are available in a fully automated report in less than 60 seconds. The entire test can easily and reliably be completed within 5 minutes.

This prediction model offers an overall accuracy of 82.4% for identifying an individual at risk of having an incident stroke within 5-years.

iPredict achieved higher accuracy than existing stroke prediction models such as Framingham and Chads scores (iPredict-stroke accuracy 82.4% compared to Framingham score 64.9%, and the CHADS2VASC score achieved 63.8% accuracy respectively on the same dataset).

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iPredict’s stroke model can be used to alert physicians of the need to take further preventive measures for these patients in the primary care setting.

The company also has AI-based screening tools for early diagnosis of diabetic retinopathy (DR), age-related macular degeneration (AMD), and glaucoma which are CE certified and TGA/Australian health approved.

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