Medalytix

Medalytix

The Medalytix IP portfolio is applicable to products that automatically detect signs of disease from digital retinal images.

The disease areas addressed by the Medalytix technology concern long-term conditions affecting large populations and incurring significant cost to healthcare systems and include.

Automated detection of diabetic retinopathy; Non-invasive screening for cardiovascular disease risk; Automated detection of AMD; Novel, objective, automated measurement approaches for use in patient monitoring and drug therapy trials

The flagship product, iGradingM, automatically detects diabetic retinopathy, the most common cause of working age blindness.

iGradingM is a proven solution for automated “disease/no disease” grading and following a successful audit phase, the first national deployment is in place for the Scottish National Diabetic Retinopathy Screening Programme.

iGradingM allows healthcare providers to easily introduce demonstrated cost-saving measures for the benefit of their patients and the wider community.

Medalytix and Digital Healthcare have agreed an exclusive global sub-licence for Digital Healthcare to market this product, and it has been seamlessly integrated into the Digital Healthcare patient management system. For further information see www.digital-healthcare.com

iGradingCVD has been designed to allow a point of care assessment of cardiovascular risk which would be more accessible to the general population and which has the potential to provide a more appropriate and individual assessment of risk, as it is based  on the state of the vasculature in the person. Medalytix have agreed an exclusive global sub-licence for iGrading CVD and other IPR and further details will be available shortly.

iGradingM

About Us

Medalytix was established in 2006, but the chain of events that led to our inception leads back much further.

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iGradingCVD

Automated GradingMedalytix' iGrading M provides an automated system with proven clinical efficacy in the assessment of digital retinal image quality and detection of diabetic eye disease.

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