Delayed Metastasis identification whether the cancer has metastasized away from the breast Delayed identification of Diabetic Retinopathy mostly in early stages
Current diagnosis relies on cost intensive imaging and labor techniques which are prone to error
Client was looking for an alternate intensive techniques that are suitable for areas with inadequate access to quality medical facilities

Our Solution

Machine learning leverages the power of many doctors to come up with a diagnosis.

Our method leverages a convolutional neural network (CNN) architecture and Deep Learning algorithms of Artificial Intelligence to discover the solution

A framework to automatically detect and localize tumors as small as 100 ×100 pixels in giga-pixel microscopy images sized 100 , 000 ×100 , 000 pixels.

Retinal Fundus images form the input of a deep neural network consisting of residual blocks, an attention layer to learn the most predictive eye features, to predict cardiovascular risk factors.

  • 30%

    Increased reach of the provider to more population

  • 15%

    Reduced cost while accommodating more requests

  • Reaching more population with less Capex