Startups use AI to close breast cancer care gaps

NVIDIA Inception startups are applying AI to gaps in breast cancer care, from screening access and radiology workload to treatment planning. Breast cancer remains the most commonly diagnosed cancer among American women, while many women over age 40 miss annual mammograms and radiology capacity is tightening as scan volumes rise.

iSono Health’s FDA-cleared ATUSA platform uses a wearable, automated 3D quantitative ultrasound system to capture standardized breast volume in approximately two minutes per breast, compared with up to 45 minutes for a conventional handheld ultrasound. Trained on thousands of full-breast scans comprising over 1.5 million ultrasound frames, the system delivers a 3D scan that the company says is 28% more sensitive than handheld 2D ultrasound, and iSono is running a multicenter study with 3,200 patients.

Whiterabbit.ai’s FDA-cleared WRDensity assesses breast density from mammograms, while WRRisk estimates long-term breast cancer risk. The company is also researching mammography AI designed to help radiologists detect more cancers, automate negative screenings and reduce avoidable callbacks.

Ataraxis AI analyzes pathology slides and clinical variables to predict treatment response and recurrence risk, addressing tests that can require a two- to four-week wait. SimBioSys builds AI tools that create 3D models of tumors and surrounding tissue and combines imaging, pathology, genomic testing when applicable and other biological inputs to support surgery and treatment decisions.