Why is this significant?

This AI software not only can assess visible features, such as brightness and grayscale, but also those invisible to the human eye such as pixel-by-pixel texture, 3D voxel texture and infinite feature weighting testing and validation.

The potential combination of AI and diagnostics could advance screening and early detection.

Why Could this Impact Care?

This machine learning algorithm assists in making a cancer diagnosis by producing a colorized map of normal and abnormal tissue. The program assigns a probability score to each lesion, which has the potential to be expanded across other cancer types (breast in design now).

This clearance shows the trend toward providing AI-assisted clinical decision support as a software-as-a-service offering to radiologists who can connect to a cloud-based server, upload the MRI, and receive an AI-generated report in less than an hour. This is a potential gamechanger to:

• increasing global access to high quality care
• decreasing health inequity due to location or socio-economic status
• providing solutions for the global lack of physicians
• enabling early diagnosis of cancer by detecting changes that are not seen by the human eye
• decreasing time from diagnosis to treatment