An FDA-cleared AI software tool that analyzes standard screening mammograms (FFDM and DBT) to detect and localize breast arterial calcifications (BAC), an under-reported incidental finding linked to cardiovascular risk. It is intended for use by radiologists interpreting screening mammograms, alongside their standard breast cancer screening workflow.

iCAD (now part of DeepHealth/RadNet) develops FDA-cleared AI software for breast cancer screening, offering AI-assisted cancer detection (ProFound Detection/ProFound AI) and breast density assessment (PowerLook Density Assessment) for digital and tomosynthesis mammography, plus an investigational AI-based breast cancer risk model; it's aimed at radiologists and breast-imaging centers reading screening/diagnostic mammograms.

Brainomix 360 is a suite of AI-powered imaging decision-support tools for acute stroke (NCCT, CTA, CTP, MRI analysis) and lung disease (CT lung imaging), plus a network-wide analytics dashboard (Vantage); it's aimed at stroke physicians/radiologists, comprehensive and primary stroke centers, stroke networks, and pulmonology/lung-disease clinical teams. The company is a University of Oxford spinout headquartered in Oxford, UK.

Harrison.ai Comprehensive Care is an AI-assisted triage and notification (CADt) platform for chest X-ray and non-contrast head CT that flags time-sensitive and incidental findings including intracranial hemorrhage subtypes, acute infarct, obstructive hydrocephalus, pneumothorax, and vertebral compression fracture to help radiologists reprioritize worklists; it's aimed at radiologists, emergency/acute care teams, teleradiology groups, and hospital administrators. The product is developed by Harrison.ai (formerly branded Annalise.ai), an Australia-headquartered company.

RapidAI is an enterprise clinical AI platform that analyzes CT and other imaging to detect and quantify vascular and neurovascular pathology including stroke, hemorrhage, aneurysm, and pulmonary embolism and routes automated alerts to care teams; it's built for radiologists, neurologists/stroke physicians, care coordination teams, IT departments, and hospital administrators managing imaging-based service lines.

The Full Brain Solution runs in the background, automatically analyzing non-contrast CT and CTA head/neck images immediately after acquisition. If the AI detects a potential acute abnormality such as a large vessel occlusion or intracranial hemorrhage, it flags the study as "high priority" in the radiologist’s worklist and sends an alert to the relevant care team (e.g., neuro-interventionalists) via a mobile app. It functions as a retrospective "safety net" and prioritization engine, ensuring critical cases are read first rather than sitting in a queue.

Lunit INSIGHT CXR analyzes frontal chest radiographs in near real-time to identify potential abnormalities. In its primary workflow, it generates an "abnormality score" (0–100%) and a secondary image (heatmap) that highlights the exact location of suspicious findings like nodules, consolidation, or pneumothorax. For US-based users utilizing the FDA-cleared "Triage" module, the system functions as a background "traffic controller," automatically flagging studies with critical findings (e.g., pneumothorax) to move them to the top of the radiologist’s worklist for immediate review.

Qure.ai’s flagship algorithm (qXR) can read a simple Chest X-Ray in seconds to detect Lung Cancer, Tuberculosis, Pneumonia, and Heart Failure. This makes it the "AI for the 99%"—critical for Urgent Care centers, rural clinics, and EDs where CT scanners aren't always the first line of defense. The platform also includes qER (for detecting brain bleeds and strokes on CT), qCT (for lung nodule quantification), and qMSK (for fracture detection), allowing health systems to deploy a single AI vendor for both their high-tech Trauma Centers and their low-tech Urgent Care clinics.

Viz.ai (Neuro) is the "Operating System" for modern stroke networks. It solves the deadly delay of "phone tag" between the ER, Radiology, and the Neurointerventionalist. By connecting directly to the CT scanner, it uses AI to detect time-sensitive pathologies (like Large Vessel Occlusions) in seconds and triggers a synchronous alert to the entire stroke team on their mobile phones. It effectively turns a linear workflow (Scan -> Read -> Call -> Page -> Call) into a parallel immediate response.