{"id":47051,"date":"2022-08-08T19:01:57","date_gmt":"2022-08-08T17:01:57","guid":{"rendered":"https:\/\/pharma-trend.com\/en\/ihealthscreen-inc-introduces-an-automated-stroke-prediction-model-based-on-ai-and-color-fundus-imaging\/"},"modified":"2022-08-08T19:01:57","modified_gmt":"2022-08-08T17:01:57","slug":"ihealthscreen-inc-introduces-an-automated-stroke-prediction-model-based-on-ai-and-color-fundus-imaging","status":"publish","type":"post","link":"https:\/\/pharma-trend.com\/en\/ihealthscreen-inc-introduces-an-automated-stroke-prediction-model-based-on-ai-and-color-fundus-imaging\/","title":{"rendered":"iHealthScreen Inc. Introduces An Automated Stroke Prediction Model, based on AI and Color Fundus Imaging"},"content":{"rendered":"
\n

\niHealthScreen is the First Company to Develop An AI- and Color-Fundus- Image-Based Stroke Prediction model, Funded by the National Institutes of Health (NIH)<\/b>\n<\/p>\n

NEW YORK–(BUSINESS WIRE)–#AI<\/a>—iPredictTM<\/sup><\/a> 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.\n<\/p>\n

<\/a><\/p>\n

\nOnce high-resolution images of the patient\u2019s eyes have been captured using a color fundus camera and submitted to the iPredictTM<\/sup><\/a> 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.\n<\/p>\n

\nThis prediction model offers an overall accuracy of 82.4% for identifying an individual at risk of having an incident stroke within 5-years.\n<\/p>\n

\niPredict 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).\n<\/p>\n

\niPredict\u2019s stroke model can be used to alert physicians of the need to take further preventive measures for these patients in the primary care setting.\n<\/p>\n

\nThe 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.\n<\/p>\n

\niHealthScreen<\/a> company is open to partnerships for distribution and\/or co-development of its products in various territories. For more information: https:\/\/www.iHealthScreen.org<\/a>\n<\/p>\n

Contacts<\/b> <\/p>\n

\nAlauddin Bhuiyan, Ph.D.
\n
CEO, iHealthScreen Inc.
\n
E: bhuiyan@ihealthscreen.org<\/a>
T: +1 718 926 9000\n<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

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) NEW YORK–(BUSINESS WIRE)–#AI—iPredictTM 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 … [Read more…]<\/a><\/span><\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[13],"tags":[],"class_list":{"0":"entry","1":"post","2":"publish","3":"author-business","4":"post-47051","6":"format-standard","7":"category-industry"},"yoast_head":"\niHealthScreen Inc. Introduces An Automated Stroke Prediction Model, based on AI and Color Fundus Imaging - Pharma Trend<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/pharma-trend.com\/en\/ihealthscreen-inc-introduces-an-automated-stroke-prediction-model-based-on-ai-and-color-fundus-imaging\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"iHealthScreen Inc. 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