End to End Lung Nodule Management
qLC-Suite
Artificial Intelligence For Early Lung Cancer Detection
2.7M+
Chest X-Rays processed globally for Lung Cancer
9/10
Missed nodules identified by radiologists using qXR
350+
Sites using qXR for early detection of Lung Cancer
46%
Faster reporting for nodules with qCT
40%
Fewer nodules missed with qXR
24%
Improvement in assigning malignancy risk using qCT
qXR
World's most widely used AI for comprehensive chest X-ray reporting, providing pre-read assistance in <1 minute with detailed lung findings.
Identify more incidental nodules from CXRs taken from non-oncology departments and help early-stage lung cancer detection
Generate patented and clinically validated Lung Nodule Malignancy (LNM) Risk Score for nodules detected to reduce false positives
Provide insights into nodule characteristics to increase confidence and accuracy for clinicians
Setup Automated Discordance framework for uninterrupted workflow, still helping find more cases
qCT
Helps in early detection and monitoring of lung nodules. Precise quantification, comprehensive characterization, and 3D visualization ensure no missed opportunities for early intervention.
Locate nodules via incidental and targeted screening
Measure volume with just 1 click
Track volumetric growth
Assign malignancy risk based on guidelines such as Lung-RADS®, Brocks, and Fleischner
qTrack
Comprehensive lung nodule management platform that enables care coordination through smart prompts, hardware-agnostic image viewing for AI-annotated Chest X-Rays and CTs, cross-departmental scan sharing, and custom notifications for suspect cases.
Access X-rays and CTs on any device in real-time with AI report
Enable sound alerts for suspect cancer cases
Share patient records across departments
Track at-risk cancer patients through smart prompts, custom workflows, and forms
Monitor program health and drop-offs through tailored dashboards
“Worldwide healthcare systems have a significant challenge in the detection of lung cancer. At present, nearly 50% of patients present with advanced or stage 4 cancer, leading to poorer outcomes. If we can spot cancer earlier, by speeding up the time and accuracy of the 100,000 chest X-rays performed each year at NHSGGC, we can improve time to further imaging, and subsequent treatment. Qure’s chest X-ray AI will help orchestrate benefits for the whole patient care pathway.”
Prof. David Lowe
Professor of Health Innovation
University of Glasgow
“AI solutions such as qXR should improve the pathway logistics by flagging abnormalities on chest X-rays as soon as they are undertaken, helping patients progress rapidly to CT scanning.”
Prof. David Baldwin
Honorary Professor of Medicine and Consultant Physician
Nottingham University Hospitals
“Incorporating AI algorithms into diagnostic pathways has showcased their transformative impact on the field of medicine. Solutions like Qure.ai's qXR-LN are a significant step towards establishing new possibilities in pulmonary imaging, particularly within oncology. The need for early-stage lung cancer detection is crucial, and tools like qXR-LN can play a significant role in the early detection of incidental nodules"
Dr. Vishisht Mehta
MBBS, FCCP, Director of Interventional Pulmonology
Comprehensive Cancer Centers of Nevada
"Our partnership with Qure.ai represents a critical step in our commitment to the EDISON Alliance's 1 Billion Lives Challenge. Lung cancer remains a major global health concern, and through applying AI to screen for lung cancer risk in millions of routine X-rays, it will provide a low-cost, high-impact way of ensuring at-risk patients enter the right diagnostic and care pathway. This milestone exemplifies our A.Catalyst Network approach to expanding access to digital healthcare and making change in the communities we serve."
Nipun Jain
Head of International A.Catalyst Network
Astrazeneca
“In our quest to drive data-driven innovations in clinical oncology, the advancements made by Qure.ai stand out. Their AI tools, particularly in radiology, align perfectly with our mission at Project Data Sphere. By collaborating with partners like Qure.ai, we can catalyze innovative ideas and transform the landscape of oncology clinical trials. Qure.ai's commitment to enhancing image analysis and assisting radiologists through AI is commendable and pivotal in accelerating clinical research and improving patient outcomes. Their work is a testament to the incredible potential of AI in revolutionizing healthcare.”
Asba Tasneem
Executive Director
Project Data Sphere
“Worldwide healthcare systems have a significant challenge in the detection of lung cancer. At present, nearly 50% of patients present with advanced or stage 4 cancer, leading to poorer outcomes. If we can spot cancer earlier, by speeding up the time and accuracy of the 100,000 chest X-rays performed each year at NHSGGC, we can improve time to further imaging, and subsequent treatment. Qure’s chest X-ray AI will help orchestrate benefits for the whole patient care pathway.”
Prof. David Lowe
Professor of Health Innovation
University of Glasgow
“AI solutions such as qXR should improve the pathway logistics by flagging abnormalities on chest X-rays as soon as they are undertaken, helping patients progress rapidly to CT scanning.”
Prof. David Baldwin
Honorary Professor of Medicine and Consultant Physician
Nottingham University Hospitals
“Incorporating AI algorithms into diagnostic pathways has showcased their transformative impact on the field of medicine. Solutions like Qure.ai's qXR-LN are a significant step towards establishing new possibilities in pulmonary imaging, particularly within oncology. The need for early-stage lung cancer detection is crucial, and tools like qXR-LN can play a significant role in the early detection of incidental nodules"
Dr. Vishisht Mehta
MBBS, FCCP, Director of Interventional Pulmonology
Comprehensive Cancer Centers of Nevada
"Our partnership with Qure.ai represents a critical step in our commitment to the EDISON Alliance's 1 Billion Lives Challenge. Lung cancer remains a major global health concern, and through applying AI to screen for lung cancer risk in millions of routine X-rays, it will provide a low-cost, high-impact way of ensuring at-risk patients enter the right diagnostic and care pathway. This milestone exemplifies our A.Catalyst Network approach to expanding access to digital healthcare and making change in the communities we serve."
Nipun Jain
Head of International A.Catalyst Network
Astrazeneca
“In our quest to drive data-driven innovations in clinical oncology, the advancements made by Qure.ai stand out. Their AI tools, particularly in radiology, align perfectly with our mission at Project Data Sphere. By collaborating with partners like Qure.ai, we can catalyze innovative ideas and transform the landscape of oncology clinical trials. Qure.ai's commitment to enhancing image analysis and assisting radiologists through AI is commendable and pivotal in accelerating clinical research and improving patient outcomes. Their work is a testament to the incredible potential of AI in revolutionizing healthcare.”
Asba Tasneem
Executive Director
Project Data Sphere
“Worldwide healthcare systems have a significant challenge in the detection of lung cancer. At present, nearly 50% of patients present with advanced or stage 4 cancer, leading to poorer outcomes. If we can spot cancer earlier, by speeding up the time and accuracy of the 100,000 chest X-rays performed each year at NHSGGC, we can improve time to further imaging, and subsequent treatment. Qure’s chest X-ray AI will help orchestrate benefits for the whole patient care pathway.”
Prof. David Lowe
Professor of Health Innovation
University of Glasgow
“AI solutions such as qXR should improve the pathway logistics by flagging abnormalities on chest X-rays as soon as they are undertaken, helping patients progress rapidly to CT scanning.”
Prof. David Baldwin
Honorary Professor of Medicine and Consultant Physician
Nottingham University Hospitals
“Incorporating AI algorithms into diagnostic pathways has showcased their transformative impact on the field of medicine. Solutions like Qure.ai's qXR-LN are a significant step towards establishing new possibilities in pulmonary imaging, particularly within oncology. The need for early-stage lung cancer detection is crucial, and tools like qXR-LN can play a significant role in the early detection of incidental nodules"
Dr. Vishisht Mehta
MBBS, FCCP, Director of Interventional Pulmonology
Comprehensive Cancer Centers of Nevada
"Our partnership with Qure.ai represents a critical step in our commitment to the EDISON Alliance's 1 Billion Lives Challenge. Lung cancer remains a major global health concern, and through applying AI to screen for lung cancer risk in millions of routine X-rays, it will provide a low-cost, high-impact way of ensuring at-risk patients enter the right diagnostic and care pathway. This milestone exemplifies our A.Catalyst Network approach to expanding access to digital healthcare and making change in the communities we serve."
Nipun Jain
Head of International A.Catalyst Network
Astrazeneca
“In our quest to drive data-driven innovations in clinical oncology, the advancements made by Qure.ai stand out. Their AI tools, particularly in radiology, align perfectly with our mission at Project Data Sphere. By collaborating with partners like Qure.ai, we can catalyze innovative ideas and transform the landscape of oncology clinical trials. Qure.ai's commitment to enhancing image analysis and assisting radiologists through AI is commendable and pivotal in accelerating clinical research and improving patient outcomes. Their work is a testament to the incredible potential of AI in revolutionizing healthcare.”
Asba Tasneem
Executive Director
Project Data Sphere
“Worldwide healthcare systems have a significant challenge in the detection of lung cancer. At present, nearly 50% of patients present with advanced or stage 4 cancer, leading to poorer outcomes. If we can spot cancer earlier, by speeding up the time and accuracy of the 100,000 chest X-rays performed each year at NHSGGC, we can improve time to further imaging, and subsequent treatment. Qure’s chest X-ray AI will help orchestrate benefits for the whole patient care pathway.”
Prof. David Lowe
Professor of Health Innovation
University of Glasgow
“AI solutions such as qXR should improve the pathway logistics by flagging abnormalities on chest X-rays as soon as they are undertaken, helping patients progress rapidly to CT scanning.”
Prof. David Baldwin
Honorary Professor of Medicine and Consultant Physician
Nottingham University Hospitals
“Incorporating AI algorithms into diagnostic pathways has showcased their transformative impact on the field of medicine. Solutions like Qure.ai's qXR-LN are a significant step towards establishing new possibilities in pulmonary imaging, particularly within oncology. The need for early-stage lung cancer detection is crucial, and tools like qXR-LN can play a significant role in the early detection of incidental nodules"
Dr. Vishisht Mehta
MBBS, FCCP, Director of Interventional Pulmonology
Comprehensive Cancer Centers of Nevada
"Our partnership with Qure.ai represents a critical step in our commitment to the EDISON Alliance's 1 Billion Lives Challenge. Lung cancer remains a major global health concern, and through applying AI to screen for lung cancer risk in millions of routine X-rays, it will provide a low-cost, high-impact way of ensuring at-risk patients enter the right diagnostic and care pathway. This milestone exemplifies our A.Catalyst Network approach to expanding access to digital healthcare and making change in the communities we serve."
Nipun Jain
Head of International A.Catalyst Network
Astrazeneca
“In our quest to drive data-driven innovations in clinical oncology, the advancements made by Qure.ai stand out. Their AI tools, particularly in radiology, align perfectly with our mission at Project Data Sphere. By collaborating with partners like Qure.ai, we can catalyze innovative ideas and transform the landscape of oncology clinical trials. Qure.ai's commitment to enhancing image analysis and assisting radiologists through AI is commendable and pivotal in accelerating clinical research and improving patient outcomes. Their work is a testament to the incredible potential of AI in revolutionizing healthcare.”
Asba Tasneem
Executive Director
Project Data Sphere
“Worldwide healthcare systems have a significant challenge in the detection of lung cancer. At present, nearly 50% of patients present with advanced or stage 4 cancer, leading to poorer outcomes. If we can spot cancer earlier, by speeding up the time and accuracy of the 100,000 chest X-rays performed each year at NHSGGC, we can improve time to further imaging, and subsequent treatment. Qure’s chest X-ray AI will help orchestrate benefits for the whole patient care pathway.”
Prof. David Lowe
Professor of Health Innovation
University of Glasgow
“AI solutions such as qXR should improve the pathway logistics by flagging abnormalities on chest X-rays as soon as they are undertaken, helping patients progress rapidly to CT scanning.”
Prof. David Baldwin
Honorary Professor of Medicine and Consultant Physician
Nottingham University Hospitals
“Incorporating AI algorithms into diagnostic pathways has showcased their transformative impact on the field of medicine. Solutions like Qure.ai's qXR-LN are a significant step towards establishing new possibilities in pulmonary imaging, particularly within oncology. The need for early-stage lung cancer detection is crucial, and tools like qXR-LN can play a significant role in the early detection of incidental nodules"
Dr. Vishisht Mehta
MBBS, FCCP, Director of Interventional Pulmonology
Comprehensive Cancer Centers of Nevada
"Our partnership with Qure.ai represents a critical step in our commitment to the EDISON Alliance's 1 Billion Lives Challenge. Lung cancer remains a major global health concern, and through applying AI to screen for lung cancer risk in millions of routine X-rays, it will provide a low-cost, high-impact way of ensuring at-risk patients enter the right diagnostic and care pathway. This milestone exemplifies our A.Catalyst Network approach to expanding access to digital healthcare and making change in the communities we serve."
Nipun Jain
Head of International A.Catalyst Network
Astrazeneca
“In our quest to drive data-driven innovations in clinical oncology, the advancements made by Qure.ai stand out. Their AI tools, particularly in radiology, align perfectly with our mission at Project Data Sphere. By collaborating with partners like Qure.ai, we can catalyze innovative ideas and transform the landscape of oncology clinical trials. Qure.ai's commitment to enhancing image analysis and assisting radiologists through AI is commendable and pivotal in accelerating clinical research and improving patient outcomes. Their work is a testament to the incredible potential of AI in revolutionizing healthcare.”
Asba Tasneem
Executive Director
Project Data Sphere
“Worldwide healthcare systems have a significant challenge in the detection of lung cancer. At present, nearly 50% of patients present with advanced or stage 4 cancer, leading to poorer outcomes. If we can spot cancer earlier, by speeding up the time and accuracy of the 100,000 chest X-rays performed each year at NHSGGC, we can improve time to further imaging, and subsequent treatment. Qure’s chest X-ray AI will help orchestrate benefits for the whole patient care pathway.”
Prof. David Lowe
Professor of Health Innovation
University of Glasgow
“AI solutions such as qXR should improve the pathway logistics by flagging abnormalities on chest X-rays as soon as they are undertaken, helping patients progress rapidly to CT scanning.”
Prof. David Baldwin
Honorary Professor of Medicine and Consultant Physician
Nottingham University Hospitals
“Incorporating AI algorithms into diagnostic pathways has showcased their transformative impact on the field of medicine. Solutions like Qure.ai's qXR-LN are a significant step towards establishing new possibilities in pulmonary imaging, particularly within oncology. The need for early-stage lung cancer detection is crucial, and tools like qXR-LN can play a significant role in the early detection of incidental nodules"
Dr. Vishisht Mehta
MBBS, FCCP, Director of Interventional Pulmonology
Comprehensive Cancer Centers of Nevada
"Our partnership with Qure.ai represents a critical step in our commitment to the EDISON Alliance's 1 Billion Lives Challenge. Lung cancer remains a major global health concern, and through applying AI to screen for lung cancer risk in millions of routine X-rays, it will provide a low-cost, high-impact way of ensuring at-risk patients enter the right diagnostic and care pathway. This milestone exemplifies our A.Catalyst Network approach to expanding access to digital healthcare and making change in the communities we serve."
Nipun Jain
Head of International A.Catalyst Network
Astrazeneca
“In our quest to drive data-driven innovations in clinical oncology, the advancements made by Qure.ai stand out. Their AI tools, particularly in radiology, align perfectly with our mission at Project Data Sphere. By collaborating with partners like Qure.ai, we can catalyze innovative ideas and transform the landscape of oncology clinical trials. Qure.ai's commitment to enhancing image analysis and assisting radiologists through AI is commendable and pivotal in accelerating clinical research and improving patient outcomes. Their work is a testament to the incredible potential of AI in revolutionizing healthcare.”
Asba Tasneem
Executive Director
Project Data Sphere
“Worldwide healthcare systems have a significant challenge in the detection of lung cancer. At present, nearly 50% of patients present with advanced or stage 4 cancer, leading to poorer outcomes. If we can spot cancer earlier, by speeding up the time and accuracy of the 100,000 chest X-rays performed each year at NHSGGC, we can improve time to further imaging, and subsequent treatment. Qure’s chest X-ray AI will help orchestrate benefits for the whole patient care pathway.”
Prof. David Lowe
Professor of Health Innovation
University of Glasgow
“AI solutions such as qXR should improve the pathway logistics by flagging abnormalities on chest X-rays as soon as they are undertaken, helping patients progress rapidly to CT scanning.”
Prof. David Baldwin
Honorary Professor of Medicine and Consultant Physician
Nottingham University Hospitals
“Incorporating AI algorithms into diagnostic pathways has showcased their transformative impact on the field of medicine. Solutions like Qure.ai's qXR-LN are a significant step towards establishing new possibilities in pulmonary imaging, particularly within oncology. The need for early-stage lung cancer detection is crucial, and tools like qXR-LN can play a significant role in the early detection of incidental nodules"
Dr. Vishisht Mehta
MBBS, FCCP, Director of Interventional Pulmonology
Comprehensive Cancer Centers of Nevada
"Our partnership with Qure.ai represents a critical step in our commitment to the EDISON Alliance's 1 Billion Lives Challenge. Lung cancer remains a major global health concern, and through applying AI to screen for lung cancer risk in millions of routine X-rays, it will provide a low-cost, high-impact way of ensuring at-risk patients enter the right diagnostic and care pathway. This milestone exemplifies our A.Catalyst Network approach to expanding access to digital healthcare and making change in the communities we serve."
Nipun Jain
Head of International A.Catalyst Network
Astrazeneca
“In our quest to drive data-driven innovations in clinical oncology, the advancements made by Qure.ai stand out. Their AI tools, particularly in radiology, align perfectly with our mission at Project Data Sphere. By collaborating with partners like Qure.ai, we can catalyze innovative ideas and transform the landscape of oncology clinical trials. Qure.ai's commitment to enhancing image analysis and assisting radiologists through AI is commendable and pivotal in accelerating clinical research and improving patient outcomes. Their work is a testament to the incredible potential of AI in revolutionizing healthcare.”
Asba Tasneem
Executive Director
Project Data Sphere
Needle in Haystack: Opportunistic Screening of Lung Nodules amidst Covid-19 using Deep Learning
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