Artificial Intelligence for Chest X-ray Interpretation

qXR detects multiple abnormal findings on a chest X-ray in less than 1 minute.

qXR can segregate abnormal scans from normal and interpret abnormalities in the lungs, pleura, mediastinum, bones, diaphragm, and heart. It can also aid clinicians with the placement and measurement of devices placed in the thorax.


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Can be deployed on-cloud or on-premises

Output available in multiple languages

Supports scans from all major manufacturers

Clinically validated in multiple geographies

Certifications

Applications

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Radiology assistance

qXR is currently used by leading hospital globally as a pre-read assistance or as a post read second reader. With deep integrations available into the radiology workflow, the visual and free text outputs are pushed back to the PACS for the reporting radiologist to review. Additionally the inttegration can be configured to send hl7 messages to the RIS.

Radiology assistance

qXR is currently used by leading hospital globally as a pre-read assistance or as a post read second reader. With deep integrations available into the radiology workflow, the visual and free text outputs are pushed back to the PACS for the reporting radiologist to review. Additionally the inttegration can be configured to send hl7 messages to the RIS.

Radiology assistance

qXR is currently used by leading hospital globally as a pre-read assistance or as a post read second reader. With deep integrations available into the radiology workflow, the visual and free text outputs are pushed back to the PACS for the reporting radiologist to review. Additionally the inttegration can be configured to send hl7 messages to the RIS.

Radiology assistance

qXR is currently used by leading hospital globally as a pre-read assistance or as a post read second reader. With deep integrations available into the radiology workflow, the visual and free text outputs are pushed back to the PACS for the reporting radiologist to review. Additionally the inttegration can be configured to send hl7 messages to the RIS.

Product Capability

qXR can detect and localize multiple findings in a chest X-ray including detection of multiple findings with the lungs, pleura, heart, bones and the diaphragm.


How it works

qXR uses deep learning technology to automate the chest X-ray interpretation process. When used as a screening tool, followed by immediate bacteriological/NAAT confirmation, qXR significantly reduces time to diagnosis.

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How we deploy



Wide variations are observed in performing carotid duplex ultrasonography as well as interpretation of the findings. Introduction of automation, image guidance and AI are needed to improve the quality, reliability and reproducibility of this important diagnostic modality for evaluating and monitoring atherosclerotic disease.

Prof Vijay Sharma

Stroke Neurologist, Singapore

Wide variations are observed in performing carotid duplex ultrasonography as well as interpretation of the findings. Introduction of automation, image guidance and AI are needed to improve the quality, reliability and reproducibility of this impor…

Dr. Hemant Deshmukh

Dean, KEM Hospital, Head of MCGM COVID-19 taskforce

When we realized that the AI-generated chest X ray results were showing the presence of COVID, this particularly helped us see some things like basal consolidation, prominent bronchial markings, markings or ground glass appearances. Using AI for a…

Dr. Clarence J Samuel

Professor-Head Dept of Community Medicine

qSCOUT an AI powered solution for comprehensive Active vaccine surveillance and AEFI monitoring…

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Jerome Triñona

Account coordinator – ACCESS TB Project, Philippine Business for Social Progress

Qure.ai’s complete TB software is very helpful in maximizing our time – now we can keep track of the entire patient workflow in one place

Dr. Shibu Vijayan

Director TB/HIV, PATH India

Qure.ai’s chest X-ray solution helps in early identification of probable TB cases and helps doctors in fast-tracking of TB patients for confirmatory diagnosis. AI will act as a force multiplier for early and fast detection

Brian Baker

Director Software Engineering, vRad

With our scale and diversity of data, a model that can operate without erroring and crashing through a single night is an engineering feat on its own

Dr. Bhujang Pai

Head of Radiology​ Seven Hills, COVID-19 centre​

At Seven Hills Hospital, we have a daily load of 200 to 250 Chest X-Rays from the admitted COVID-19 cases, sometimes going upto 300 films per day. Having qXR has helped me immensely in reading them in a much shorter amount of time, which helps me …

Dr. Hemant Deshmukh

Dean, KEM Hospital​ Head of MCGM ​ COVID-19 taskforce​

When we realised that the AI generated chest X ray results were showing presence of COVID, this particularly helped us see something like basal consolidation, prominent bronchial markings, markings or ground glass appearance on chest X-Ray. These …

Dr. Shibu Vijayan

Global Director TB/HIV, PATH​

Qure.ai’s chest X-ray solution helps in early identification of probable TB cases and helps doctors in fast-tracking of TB patients for confirmatory diagnosis. AI will act as a force multiplier for early and fast detection” ​

Speaking about the…

Dr. Jemin Webster

physician at Tezpur

qER is good as it alerts the physicians in a busy casualty room even without having to open the workstation. We know if there are any critical issues with the patient.

Dr. A.T. Prabhakar

Professor (Neurology); Christian Medical College, Vellore

Today, most sonography results are very operator-dependent. Additionally, for a carotid doppler, it is time-consuming to make all the measurements (IMT, CAS doppler, stenosis grading, etc.).

AI-assisted guidance & interpretation will reduce…

Kevin Terrins

Director of Business Development at Medica PLC

Qure.ai have proven themselves to be a great partner, working alongside the team at Medica Group Plc as we took our first steps in AI

Florentino Bernardo

CIO, Grupo Empresarial Angeles

We were impressed with the seamless set-up of the algorithm allowing us to test it with very little effort and get immediate results. We also realized how easy the algorithms quantification methods make it to follow up with a patient’s improvement…

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