Vision loss and eye health issues are a growing concern, affecting millions. A 2016 report from the National Academies of Sciences, Engineering, and Medicine estimates that 90 million Americans over 40 experience vision problems, including blindness, macular degeneration, cataracts, and diabetic eye disease. Unfortunately, current vision tests often don’t fully capture what people are seeing, making it hard to track changes in vision over time—a major challenge for healthcare systems.
To address this, we’re using artificial intelligence (AI) to revolutionize vision testing. By applying advanced AI techniques, we’ve developed new tests that assess aspects like sharpness, contrast sensitivity, visual field, and reading ability. These tests are more accurate and efficient than traditional ones and have already been adopted in hundreds of clinical research and trial sites. They’ve even uncovered vision loss that traditional tests missed, proving their value for both patient care and research.
We’re also using AI models to improve test precision by combining results from multiple tests, helping doctors make more informed decisions. These models can predict how patients might respond to treatment and identify those at risk for eye diseases, tracking condition progression and predicting outcomes.
Our goal is to create a cutting-edge platform that integrates various tests, algorithms, and AI to make vision assessments more precise. By enhancing decision-making in clinical trials and patient care, we aim to improve eye health worldwide.
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