| Title: | A Machine Learning based screening system for Retinal and Systemic Diseases |
| Lead Institution: | iHealthScreen Inc |
| Principal investigator: | Dr Alauddin Bhuiyan |
Application 44226
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About
Latest advances in machine learning, specifically the deep learning technique have shown tremendous potential in medical applications for diagnosing and detecting diseases at early stage based on imaging data. In this research project, we aim to make use of these advances to automatically identify people at risk of certain eye and systemic diseases such as Diabetic Retinopathy, Age-related Macular Degeneration, Stroke and Cardiovascular diseases at early stage and help prevention. For example, the number of Americans with diabetic retinopathy is expected to rise from 7.7 million to 14.6 million between 2010 and 2050. It is estimated that nearly 80% of these cases can be preventable. Similarly, By 2050, the estimated number of people with AMD is expected to more than double from 2.07 million to 5.44 million. Early detection is key to prevent these diseases and reducing the unnecessary overhead of medical bills, and save sight and lives. The project will make use of the vast imaging and demographic data that UK Biobank has, to build such systems to predict the onset of these diseases. We estimate that it will take up to two years to complete the research project.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 15565 | A Machine Learning Prediction Model to Identify Individuals at Risk of 5-Year Incident Stroke Based on Retinal Imaging | Arun Govindaiah (+4) | 2025 | Sensors |
Enabling scientific discoveries that improve human health