Qure.ai Radiology AI

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Qure.ai provides FDA-cleared AI solutions for radiology, supporting TB detection, lung cancer screening, and stroke care across 105+ countries and 5,200+ clinical sites.

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AI Models & Infrastructure

Research & Education

About

Qure.ai is the world's most adopted healthcare AI platform, delivering AI-assisted radiology solutions designed to make diagnostic care more accessible, timely, and accurate. Built on a training dataset of over 1 billion medical images, its deep learning models support clinical decision-making for some of the world's most pressing health challenges. The platform offers three major care pathways: tuberculosis detection (including pediatric TB and silicosis), lung cancer screening, and stroke care coordination. Its WHO-evaluated AI solutions for TB support real-time disease surveillance and clinical triage in low-resource settings. For lung health, Qure.ai enables end-to-end care from nodule detection to progression tracking, supporting both hospitals and pharmaceutical research. Its stroke suite provides an AI-powered coordination layer for hub-and-spoke hospital networks, ensuring patients receive timely intervention. Qure.ai's FDA-cleared products integrate seamlessly with existing X-ray hardware—old or new—making deployment practical even in resource-constrained environments. The platform is trusted by global healthcare leaders including AstraZeneca, Medtronic, and NHS Trusts, and recognized by TIME among its 100 Most Influential Companies of 2025. It is purpose-built for healthcare institutions, national health programs, and pharmaceutical organizations seeking to improve patient outcomes at scale.

Key Features

Tuberculosis & Silicosis Detection: WHO-evaluated AI analyzes chest X-rays to flag TB, pediatric TB, and silicosis, enabling real-time disease surveillance and faster clinical referrals in any setting.
Lung Cancer Screening & Nodule Tracking: End-to-end lung cancer care continuum that detects nodules early, measures disease progression over time, and integrates into clinical and pharmaceutical workflows.
Stroke Care Coordination: AI-powered triage and real-time communication suite enabling Hub & Spoke hospital networks to coordinate stroke interventions within the critical treatment window.
Hardware-Agnostic Integration: Compatible with existing X-ray systems—old or new—allowing health facilities to deploy AI diagnostics without replacing costly equipment infrastructure.
1B+ Image Training Dataset: Models trained on over one billion medical imaging data points, delivering clinically validated accuracy across diverse patient populations and geographies.

Use Cases

National TB programs using AI-assisted chest X-ray screening to accelerate case detection and reduce diagnostic backlogs in high-burden countries.
Hospital radiology departments deploying lung nodule detection to flag early-stage lung cancer and track progression across patient follow-up visits.
Stroke networks using Qure.ai's care coordination suite to triage and transfer patients between hub and spoke hospitals within the critical treatment window.
Pharmaceutical companies integrating Qure.ai into clinical trials to measure lung health outcomes and validate drug efficacy using AI-based imaging biomarkers.
Low-resource health facilities in developing nations leveraging Qure.ai on existing X-ray hardware to provide specialist-level diagnostic support without on-site radiologists.

Pros

Massive Real-World Validation: Deployed in 5,200+ sites across 105+ countries with 40M+ lives impacted, demonstrating proven scalability and clinical effectiveness in diverse settings.
Regulatory & Clinical Credibility: FDA-cleared across multiple indications and WHO-evaluated for TB, providing institutional-grade trust for hospital procurement and government health programs.
Works With Existing Infrastructure: Designed to integrate with legacy X-ray hardware, removing the barrier of capital equipment upgrades for under-resourced health systems.
Multi-Condition Coverage: A single AI platform addresses several high-burden diseases—TB, lung cancer, and stroke—providing breadth for health systems managing multiple priorities.

Cons

Radiology-Specific Scope: Focused exclusively on medical imaging use cases; not applicable to general clinical documentation, patient management, or non-imaging diagnostic workflows.
Enterprise Pricing with No Public Tiers: Pricing is not publicly disclosed and is tailored for healthcare institutions, making it difficult for smaller clinics or individual providers to evaluate cost upfront.
Requires Clinical Oversight: As a clinical decision support tool, it must be used alongside trained medical professionals and cannot replace radiologist review in regulated environments.

Frequently Asked Questions

Qure.ai uses deep learning AI to analyze medical images—primarily chest X-rays and CT scans—to assist clinicians in diagnosing conditions like tuberculosis, lung cancer, and stroke, improving both speed and accuracy of diagnosis.

Yes. Qure.ai has received FDA clearance for multiple indications, including several chest X-ray findings. As of early 2026, the company has received six additional new FDA-cleared indications.

Qure.ai supports detection and monitoring of tuberculosis (including pediatric TB), silicosis, lung nodules and cancer, and stroke. Its chest X-ray AI (qXR) covers a broad range of thoracic findings.

Qure.ai is deployed in over 105 countries through more than 5,200 clinical sites, making it one of the most globally distributed healthcare AI platforms in the world.

Yes. Qure.ai is designed to be hardware-agnostic and integrates with both new and legacy X-ray systems, enabling facilities to add AI diagnostics without replacing their existing equipment.