MedAI Verdict
Radiology

AI Radiology

Qure.ai

by Qure.ai  ·  IN

Last verified

AI for chest X-ray (qXR), head CT (qER) and lung nodule CT, with TB screening. The homepage cites sites across 107 countries.

Visit Qure.aiRead our methodology

At a glance

Pricing
No public price. Grant funding is not stated on Qure pages.
HIPAA
Not disclosed
SOC 2
Not disclosed
EHRs
—
Founded
—
HQ
IN
On this page

Independent score  ·  By our public rubric

49/100Solid choice
How it’s computed →
  • Regulatory & Compliance
    18/28

    FDA cleared (10 K-numbers on record)

  • Clinical Integration
    0/26

    No EHR integrations listed

  • Evidence Strength
    26/26

    5 peer-reviewed papers

  • Vendor & Market
    8.4/18

    Mid-tier funding and adoption

  • Sentiment & Transparency
    2.5/14

    Pricing on request, no public amounts

▸ Show all 11 dimensions

Regulatory & Compliance

  • FDA clearance18/18

    FDA cleared (10 K-numbers on record)

  • HIPAA / SOC2 / BAA0/10

    No public HIPAA/SOC2/BAA attestation

Clinical Integration

  • EHR integrations (count)0/14

    No EHR integrations listed

  • Top-3 EHR coverage (Epic / Oracle / Athena)0/8

    None of the top-3 EHRs covered

  • Bidirectional write-back0/4

    No bidirectional write-back documented

Evidence Strength

  • Peer-reviewed papers18/18

    5 peer-reviewed papers

  • RCT / meta-analysis / systematic review8/8

    1 RCT/Meta-Analysis/Systematic Review

Vendor & Market

  • Funding & adoption signal8/12

    Mid-tier funding and adoption

  • Years in market0/6

    Founded year not recorded

Sentiment & Transparency

  • Clinician sentiment (Reddit)0/9

    No clinician sentiment data available

  • Pricing transparency3/5

    Pricing on request, no public amounts

Scored October 15, 2026 · Public scoring method v1.1.0

Bottom line

AI for chest X-ray (qXR), head CT (qER) and lung nodule CT, with TB screening. The homepage cites sites across 107 countries.

No public price. Grant funding is not stated on Qure pages.

Editorial review  ·  By MedAI Verdict

Bottom line

Qure.ai sells deep-learning software for chest X-ray, head CT, lung nodule CT and musculoskeletal imaging, and it is best known for TB screening. It holds ten FDA 510(k) clearances, including a lung nodule product for chest radiographs. TB screening has WHO endorsement and CE marking but no FDA clearance. Independent evidence shows high sensitivity with modest specificity at one TB threshold, and RADICAL, a trial in NHS Greater Glasgow and Clyde, has published only a protocol. Hospitals and TB screening programs are the natural buyers. A department that needs peer-reviewed outcome data in its own patient mix will find little of it yet.

What is Qure.ai and who sells it?

Qure.ai Technologies is in Mumbai and was founded in 2016 by Prashant Warier (CEO) and Pooja Rao. Tracxn lists Rao as a former co-founder. It raised a $65M Series D in September 2024, led by Lightspeed and 360 ONE Asset, with Merck GHI, Kae Capital, Novo Holdings, Health Quad and TeamFund (Radiology Business). Tracxn puts total funding near $139M, though that comes from a single aggregator. Qure.ai also lists a partnership with Microsoft for its US lung nodule suite. The Series D release states an intent to acquire med-tech companies.

What does it do?

The product families are qXR for chest X-ray, qER for head CT, qCT for lung nodule CT and qMSK. The homepage now focuses on "end-to-end healthcare AI for early lung nodule care" (Qure.ai website, October 2026). qXR-LN detects lung nodules on frontal adult chest radiographs, and the FDA letter covers use by radiologists, pulmonologists and emergency physicians. qCT LN Quant does nodule volumetry and tracking. qER triages head CT for intracranial hemorrhage and related findings. Other modules cover pneumothorax and effusion triage, breathing-tube position and cardiothoracic ratio.

Qure.ai says it integrates with PACS, EMR, dictation and local reporting systems but names no vendors. For HIPAA, images are de-identified before cloud processing, or the software runs on premises inside the covered entity. The company lists ISO 27001, ISO 13485:2016, MDSAP and IEC 62304, with hosting on AWS and Azure. SOC 2 and HITRUST are not stated (Qure.ai regulatory page).

What is cleared and where?

The FDA 510(k) database lists ten records for Qure.Ai Technologies as of October 2026, all substantially equivalent. They run from qER in June 2020 to qCT Lung v1.0 in September 2026, and include qXR-LN (K231805, December 2023), qCT LN Quant (K240740, August 2024) and qXR-Detect (K251934, January 2026). TB screening has no FDA clearance in those records. Qure.ai reports WHO endorsement of its chest X-ray solution for TB screening without a human reader (2021) and a CE mark for children under 3, reported in October 2025 (MedGate Today).

CE classes are IIa under the old directive for qXR v3.1 and qER v2.0 and IIb under MDR for qXR v4.0, qER-NCCT, qCT and qMSK. Qure.ai cites sites in 107 countries on its homepage and registration in more than 85 countries on its regulatory page.

What does the evidence say?

The independent record is sparse and mostly about TB. A 12-product TB evaluation put qXR v3 at 95.5% sensitivity with 48.7% specificity at one threshold (ResearchGate). A qualitative NHS evaluation found radiologists worried about missed subtle abnormalities, though staff later felt the pathway performed better than expected (PMC13527979). The Scottish Health Technology Group found evidence gaps for AI chest X-ray in suspected lung cancer.

The RADICAL protocol, a stepped-wedge study of qXR for chest X-ray triage in NHS Greater Glasgow and Clyde, was published in BMJ Open in 2024 (PMID 39306349). Results have not been published. A narrative Cureus review of qXR (PMID 38962585) is low-level evidence.

How much does Qure.ai cost?

Qure.ai quotes are not published on its website (October 2026).

How does it compare?

Lunit, Annalise.ai, Aidoc, Behold.ai and Rad AI are the usual alternatives, and CAD4TB competes for TB screening. Qure.ai's cleared lung nodule product for chest radiographs and its head CT triage give it clearer US scope than Lunit's chest X-ray, whose clearance is triage only.

The verdict

A national or regional TB program should evaluate qXR, on its own patient population, with the software version, the threshold and the process for version changes written into the contract. A US hospital should name the exact module it is buying and match it to a K-number before signing, because TB screening is not among the cleared products.

Editorial review last generated October 15, 2026. Synthesized from clinician sentiment, peer-reviewed coverage, and our editorial silo picks. Refined by hand where vendor facts change.

Pricing

What it costs

All tiers are custom-quoted. The vendor does not publish per-provider list pricing.

TierMonthlyAnnualNotes
Enterprise——No public price. Grant funding is not stated on Qure pages.

Source: vendor pricing page. Last checked October 15, 2026.

Compliance + integration

What deploys cleanly

Carries FDA 510(k) (multiple), CE Mark (MDD Class IIa, MDR Class IIb), ISO 13485:2016, ISO/IEC 27001, MDSAP per vendor documentation. Independent attestation review is the buyer's responsibility before clinical deployment.

Peer-reviewed coverage

What the literature says

5 peer-reviewed studies indexed on PubMed evaluate Qure.ai in clinical contexts. The most relevant are shown below, ranked by editorial relevance score combining title match, study design, recency, and journal tier.

Radiograph accelerated detection and identification of cancer in the lung (RADICAL): a mixed methods study to assess the clinical effectiveness and acceptability of Qure.ai artificial intelligence software to prioritise chest X-ray (CXR) interpretation.
Duncan SF, McConnachie A, Blackwood J, et al.· BMJ Open· 2024
Diagnosing and treating lung cancer in early stages is essential for survival outcomes. The chest X-ray (CXR) remains the primary screening tool to identify lung cancers in the UK; however, there is a shortfall of radiologists, while demand continues to increase. Image analysis by machine-learning software has the potential to support radiology workflows with a focus on immediate triage of suspicious X-rays. The RADICAL study will evaluate Qure.ai's 'qXR' software in reducing reporting time for suspicious X-rays in NHS Greater Glasgow & Clyde. This is a stepped-wedge cluster-randomised study…
Revolutionizing Healthcare: Qure.AI's Innovations in Medical Diagnosis and Treatment.
Zavaleta-Monestel E, Quesada-Villaseñor R, Arguedas-Chacón S, et al.· Cureus· 2024
Qure.AI, a leading company in artificial intelligence (AI) applied to healthcare, has developed a suite of innovative solutions to revolutionize medical diagnosis and treatment. With a plethora of FDA-approved tools for clinical use, Qure.AI continually strives for innovation in integrating AI into healthcare systems. This article delves into the efficacy of Qure.AI's chest X-ray interpretation tool, "qXR," in medicine, drawing from a comprehensive review of clinical trials conducted by various institutions. Key applications of AI in healthcare include machine learning, deep learning, an…
A systematic review and meta-analysis of artificial intelligence software for tuberculosis diagnosis using chest X-ray imaging.
Han ZL, Zhang YY, Li J, et al.· J Thorac Dis· 2025Systematic Review
Pulmonary tuberculosis (PTB) remains a global public health challenge, with 10.8 million new cases reported in 2023. Early diagnosis is crucial for controlling its spread, yet traditional sputum-based tests face limitations in turnaround time and resource availability. Chest X-ray (CXR) is a cost-effective diagnostic tool, but its use in high-tuberculosis (TB) burden regions is restricted by a shortage of radiologists. Artificial intelligence (AI)-based computer-aided detection (CAD) systems, leveraging deep learning, offer a promising solution for automated PTB detection. However, variabilit…
A Case Series From a Multicentric Study: Can Artificial Intelligence (AI)-Enabled Chest X-Ray Assist in the Incidental Detection of Early-Stage Lung Cancers?
Koksal D, Govindarajan A, Baykan A, et al.· Cureus· 2026Case Report
Lung cancer is the leading cause of cancer-related deaths worldwide. Early diagnosis is challenging, as patients are often asymptomatic. Low-dose computed tomography (LDCT) based screening has been shown to reduce mortality in high-risk individuals, but adoption is limited to a few countries. Chest X-ray is the most commonly used imaging modality in healthcare settings. Lung cancer can present as nodules on chest X-ray in the initial stages. Pulmonary nodules are often missed on routine chest X-rays. Artificial Intelligence (AI)-based chest X-ray software has shown promise in identifying…
Tuberculosis Disease Severity Assessment Using Clinical Variables and Radiology Enabled by Artificial Intelligence.
Ghanem M, Srivastava R, Ektefaie Y, et al.· J Infect Dis· 2026
Chest X-ray (CXR) can assess pulmonary tuberculosis (TB) severity and may guide duration of treatment. However, the optimal radiological metric and its integration with clinical variables for predicting treatment outcomes remains unclear. We used logistic regression to associate human-read and commercial artificial intelligence-generated CXR metrics with unfavorable outcome in the TB Portals real-world dataset (n = 2809). We assessed the standalone predictive accuracy for each of 10 radiological features for unfavorable outcomes, and combined the best-performing features with other clinical d…

See all on PubMed

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