From Image
to Intervention
FDA-cleared lung cancer AI that flags nodules, stratifies malignancy risk on CT, and closes the loop on follow-up – trusted and deployed worldwide with leading health systems and across global care networks.
For conditions such as intracranial hemorrhage, time is of the essence and those precious minutes can be life-changing for our patients. We have done extensive validation of the Qure.ai qER solution and are excited to continue to partner with Qure.ai and improve care for our patients.
Benjamin W. Strong
MD and Chief Medical Officer
vRad
A multicenter publication on missed and mislabeled chest radiography findings including pneumothoraces and pleural effusions reported up to 96% sensitivity and 100% specificity for the qXR algorithm.
Dr Subba Digumarthy, MD
Attending Radiologist, Thoracic Imaging, Massachusetts General Hospital
Associate Professor, Harvard Medical School
As an Emergency Medicine Physician, I have 4 to 5 patients undergoing various imaging studies at any time. The AI's ability to rapidly triage pneumothorax dramatically improves my speed and efficiency by alerting me to critical pathology far before a radiologist, or I personally have time to review the film.
Neil Roy
MD, MBA, FACEP, CPE; Chief Medical Officer
Shady Grove Medical Center
The collaboration between Qure.ai and Nuance helps make cutting-edge imaging AI easily integrated and accessible to different stakeholders in the US healthcare system. We’re excited to work together to bring scalable diagnostics solutions for providers and patients across the country.
Roland Dias
Vice President and General Manager
Nuance Precision Imaging Network
Medical imaging AI holds immense potential in the battle against lung cancer in the United States. It is great to see the breadth of FDA clearances rolling in to enable the exploration and activation of algorithms that can support radiologists and pulmonologists. This will help to detect lung nodules earlier using chest X-ray, and also analyze them in detail on chest CT.
Dr. Javier Zulueta
MD, Chief, Division of Pulmonary, Critical Care and Sleep Medicine at Mount Sinai Morningside, New York
AI serves as an additional set of eyes for radiologists, enhancing detection by flagging lung nodules that may require further evaluation. This AI-driven approach may aid in identifying more nodules which we hope supports patient care and enables us to evaluate the broader impact of medical imaging AI. The clinical trial will evaluate how many patients require follow-up CT scans, biopsies, and how many more lung cancer cases are diagnosed earlier using AI. The hope is that this clinical trial will not only advance early detection but also drive meaningful transformation in lung cancer surveillance
Amit Gupta
Cardiothoracic Radiologist and Modality Director of Diagnostic Radiography at University Hospitals Cleveland Medical Center
For conditions such as intracranial hemorrhage, time is of the essence and those precious minutes can be life-changing for our patients. We have done extensive validation of the Qure.ai qER solution and are excited to continue to partner with Qure.ai and improve care for our patients.
Benjamin W. Strong
MD and Chief Medical Officer
vRad
A multicenter publication on missed and mislabeled chest radiography findings including pneumothoraces and pleural effusions reported up to 96% sensitivity and 100% specificity for the qXR algorithm.
Dr Subba Digumarthy, MD
Attending Radiologist, Thoracic Imaging, Massachusetts General Hospital
Associate Professor, Harvard Medical School
As an Emergency Medicine Physician, I have 4 to 5 patients undergoing various imaging studies at any time. The AI's ability to rapidly triage pneumothorax dramatically improves my speed and efficiency by alerting me to critical pathology far before a radiologist, or I personally have time to review the film.
Neil Roy
MD, MBA, FACEP, CPE; Chief Medical Officer
Shady Grove Medical Center
The collaboration between Qure.ai and Nuance helps make cutting-edge imaging AI easily integrated and accessible to different stakeholders in the US healthcare system. We’re excited to work together to bring scalable diagnostics solutions for providers and patients across the country.
Roland Dias
Vice President and General Manager
Nuance Precision Imaging Network
Medical imaging AI holds immense potential in the battle against lung cancer in the United States. It is great to see the breadth of FDA clearances rolling in to enable the exploration and activation of algorithms that can support radiologists and pulmonologists. This will help to detect lung nodules earlier using chest X-ray, and also analyze them in detail on chest CT.
Dr. Javier Zulueta
MD, Chief, Division of Pulmonary, Critical Care and Sleep Medicine at Mount Sinai Morningside, New York
AI serves as an additional set of eyes for radiologists, enhancing detection by flagging lung nodules that may require further evaluation. This AI-driven approach may aid in identifying more nodules which we hope supports patient care and enables us to evaluate the broader impact of medical imaging AI. The clinical trial will evaluate how many patients require follow-up CT scans, biopsies, and how many more lung cancer cases are diagnosed earlier using AI. The hope is that this clinical trial will not only advance early detection but also drive meaningful transformation in lung cancer surveillance
Amit Gupta
Cardiothoracic Radiologist and Modality Director of Diagnostic Radiography at University Hospitals Cleveland Medical Center
For conditions such as intracranial hemorrhage, time is of the essence and those precious minutes can be life-changing for our patients. We have done extensive validation of the Qure.ai qER solution and are excited to continue to partner with Qure.ai and improve care for our patients.
Benjamin W. Strong
MD and Chief Medical Officer
vRad
A multicenter publication on missed and mislabeled chest radiography findings including pneumothoraces and pleural effusions reported up to 96% sensitivity and 100% specificity for the qXR algorithm.
Dr Subba Digumarthy, MD
Attending Radiologist, Thoracic Imaging, Massachusetts General Hospital
Associate Professor, Harvard Medical School
As an Emergency Medicine Physician, I have 4 to 5 patients undergoing various imaging studies at any time. The AI's ability to rapidly triage pneumothorax dramatically improves my speed and efficiency by alerting me to critical pathology far before a radiologist, or I personally have time to review the film.
Neil Roy
MD, MBA, FACEP, CPE; Chief Medical Officer
Shady Grove Medical Center
The collaboration between Qure.ai and Nuance helps make cutting-edge imaging AI easily integrated and accessible to different stakeholders in the US healthcare system. We’re excited to work together to bring scalable diagnostics solutions for providers and patients across the country.
Roland Dias
Vice President and General Manager
Nuance Precision Imaging Network
Medical imaging AI holds immense potential in the battle against lung cancer in the United States. It is great to see the breadth of FDA clearances rolling in to enable the exploration and activation of algorithms that can support radiologists and pulmonologists. This will help to detect lung nodules earlier using chest X-ray, and also analyze them in detail on chest CT.
Dr. Javier Zulueta
MD, Chief, Division of Pulmonary, Critical Care and Sleep Medicine at Mount Sinai Morningside, New York
AI serves as an additional set of eyes for radiologists, enhancing detection by flagging lung nodules that may require further evaluation. This AI-driven approach may aid in identifying more nodules which we hope supports patient care and enables us to evaluate the broader impact of medical imaging AI. The clinical trial will evaluate how many patients require follow-up CT scans, biopsies, and how many more lung cancer cases are diagnosed earlier using AI. The hope is that this clinical trial will not only advance early detection but also drive meaningful transformation in lung cancer surveillance
Amit Gupta
Cardiothoracic Radiologist and Modality Director of Diagnostic Radiography at University Hospitals Cleveland Medical Center
For conditions such as intracranial hemorrhage, time is of the essence and those precious minutes can be life-changing for our patients. We have done extensive validation of the Qure.ai qER solution and are excited to continue to partner with Qure.ai and improve care for our patients.
Benjamin W. Strong
MD and Chief Medical Officer
vRad
A multicenter publication on missed and mislabeled chest radiography findings including pneumothoraces and pleural effusions reported up to 96% sensitivity and 100% specificity for the qXR algorithm.
Dr Subba Digumarthy, MD
Attending Radiologist, Thoracic Imaging, Massachusetts General Hospital
Associate Professor, Harvard Medical School
As an Emergency Medicine Physician, I have 4 to 5 patients undergoing various imaging studies at any time. The AI's ability to rapidly triage pneumothorax dramatically improves my speed and efficiency by alerting me to critical pathology far before a radiologist, or I personally have time to review the film.
Neil Roy
MD, MBA, FACEP, CPE; Chief Medical Officer
Shady Grove Medical Center
The collaboration between Qure.ai and Nuance helps make cutting-edge imaging AI easily integrated and accessible to different stakeholders in the US healthcare system. We’re excited to work together to bring scalable diagnostics solutions for providers and patients across the country.
Roland Dias
Vice President and General Manager
Nuance Precision Imaging Network
Medical imaging AI holds immense potential in the battle against lung cancer in the United States. It is great to see the breadth of FDA clearances rolling in to enable the exploration and activation of algorithms that can support radiologists and pulmonologists. This will help to detect lung nodules earlier using chest X-ray, and also analyze them in detail on chest CT.
Dr. Javier Zulueta
MD, Chief, Division of Pulmonary, Critical Care and Sleep Medicine at Mount Sinai Morningside, New York
AI serves as an additional set of eyes for radiologists, enhancing detection by flagging lung nodules that may require further evaluation. This AI-driven approach may aid in identifying more nodules which we hope supports patient care and enables us to evaluate the broader impact of medical imaging AI. The clinical trial will evaluate how many patients require follow-up CT scans, biopsies, and how many more lung cancer cases are diagnosed earlier using AI. The hope is that this clinical trial will not only advance early detection but also drive meaningful transformation in lung cancer surveillance
Amit Gupta
Cardiothoracic Radiologist and Modality Director of Diagnostic Radiography at University Hospitals Cleveland Medical Center
For conditions such as intracranial hemorrhage, time is of the essence and those precious minutes can be life-changing for our patients. We have done extensive validation of the Qure.ai qER solution and are excited to continue to partner with Qure.ai and improve care for our patients.
Benjamin W. Strong
MD and Chief Medical Officer
vRad
A multicenter publication on missed and mislabeled chest radiography findings including pneumothoraces and pleural effusions reported up to 96% sensitivity and 100% specificity for the qXR algorithm.
Dr Subba Digumarthy, MD
Attending Radiologist, Thoracic Imaging, Massachusetts General Hospital
Associate Professor, Harvard Medical School
As an Emergency Medicine Physician, I have 4 to 5 patients undergoing various imaging studies at any time. The AI's ability to rapidly triage pneumothorax dramatically improves my speed and efficiency by alerting me to critical pathology far before a radiologist, or I personally have time to review the film.
Neil Roy
MD, MBA, FACEP, CPE; Chief Medical Officer
Shady Grove Medical Center
The collaboration between Qure.ai and Nuance helps make cutting-edge imaging AI easily integrated and accessible to different stakeholders in the US healthcare system. We’re excited to work together to bring scalable diagnostics solutions for providers and patients across the country.
Roland Dias
Vice President and General Manager
Nuance Precision Imaging Network
Medical imaging AI holds immense potential in the battle against lung cancer in the United States. It is great to see the breadth of FDA clearances rolling in to enable the exploration and activation of algorithms that can support radiologists and pulmonologists. This will help to detect lung nodules earlier using chest X-ray, and also analyze them in detail on chest CT.
Dr. Javier Zulueta
MD, Chief, Division of Pulmonary, Critical Care and Sleep Medicine at Mount Sinai Morningside, New York
AI serves as an additional set of eyes for radiologists, enhancing detection by flagging lung nodules that may require further evaluation. This AI-driven approach may aid in identifying more nodules which we hope supports patient care and enables us to evaluate the broader impact of medical imaging AI. The clinical trial will evaluate how many patients require follow-up CT scans, biopsies, and how many more lung cancer cases are diagnosed earlier using AI. The hope is that this clinical trial will not only advance early detection but also drive meaningful transformation in lung cancer surveillance
Amit Gupta
Cardiothoracic Radiologist and Modality Director of Diagnostic Radiography at University Hospitals Cleveland Medical Center
For conditions such as intracranial hemorrhage, time is of the essence and those precious minutes can be life-changing for our patients. We have done extensive validation of the Qure.ai qER solution and are excited to continue to partner with Qure.ai and improve care for our patients.
Benjamin W. Strong
MD and Chief Medical Officer
vRad
A multicenter publication on missed and mislabeled chest radiography findings including pneumothoraces and pleural effusions reported up to 96% sensitivity and 100% specificity for the qXR algorithm.
Dr Subba Digumarthy, MD
Attending Radiologist, Thoracic Imaging, Massachusetts General Hospital
Associate Professor, Harvard Medical School
As an Emergency Medicine Physician, I have 4 to 5 patients undergoing various imaging studies at any time. The AI's ability to rapidly triage pneumothorax dramatically improves my speed and efficiency by alerting me to critical pathology far before a radiologist, or I personally have time to review the film.
Neil Roy
MD, MBA, FACEP, CPE; Chief Medical Officer
Shady Grove Medical Center
The collaboration between Qure.ai and Nuance helps make cutting-edge imaging AI easily integrated and accessible to different stakeholders in the US healthcare system. We’re excited to work together to bring scalable diagnostics solutions for providers and patients across the country.
Roland Dias
Vice President and General Manager
Nuance Precision Imaging Network
Medical imaging AI holds immense potential in the battle against lung cancer in the United States. It is great to see the breadth of FDA clearances rolling in to enable the exploration and activation of algorithms that can support radiologists and pulmonologists. This will help to detect lung nodules earlier using chest X-ray, and also analyze them in detail on chest CT.
Dr. Javier Zulueta
MD, Chief, Division of Pulmonary, Critical Care and Sleep Medicine at Mount Sinai Morningside, New York
AI serves as an additional set of eyes for radiologists, enhancing detection by flagging lung nodules that may require further evaluation. This AI-driven approach may aid in identifying more nodules which we hope supports patient care and enables us to evaluate the broader impact of medical imaging AI. The clinical trial will evaluate how many patients require follow-up CT scans, biopsies, and how many more lung cancer cases are diagnosed earlier using AI. The hope is that this clinical trial will not only advance early detection but also drive meaningful transformation in lung cancer surveillance
Amit Gupta
Cardiothoracic Radiologist and Modality Director of Diagnostic Radiography at University Hospitals Cleveland Medical Center
For conditions such as intracranial hemorrhage, time is of the essence and those precious minutes can be life-changing for our patients. We have done extensive validation of the Qure.ai qER solution and are excited to continue to partner with Qure.ai and improve care for our patients.
Benjamin W. Strong
MD and Chief Medical Officer
vRad
A multicenter publication on missed and mislabeled chest radiography findings including pneumothoraces and pleural effusions reported up to 96% sensitivity and 100% specificity for the qXR algorithm.
Dr Subba Digumarthy, MD
Attending Radiologist, Thoracic Imaging, Massachusetts General Hospital
Associate Professor, Harvard Medical School
As an Emergency Medicine Physician, I have 4 to 5 patients undergoing various imaging studies at any time. The AI's ability to rapidly triage pneumothorax dramatically improves my speed and efficiency by alerting me to critical pathology far before a radiologist, or I personally have time to review the film.
Neil Roy
MD, MBA, FACEP, CPE; Chief Medical Officer
Shady Grove Medical Center
The collaboration between Qure.ai and Nuance helps make cutting-edge imaging AI easily integrated and accessible to different stakeholders in the US healthcare system. We’re excited to work together to bring scalable diagnostics solutions for providers and patients across the country.
Roland Dias
Vice President and General Manager
Nuance Precision Imaging Network
Medical imaging AI holds immense potential in the battle against lung cancer in the United States. It is great to see the breadth of FDA clearances rolling in to enable the exploration and activation of algorithms that can support radiologists and pulmonologists. This will help to detect lung nodules earlier using chest X-ray, and also analyze them in detail on chest CT.
Dr. Javier Zulueta
MD, Chief, Division of Pulmonary, Critical Care and Sleep Medicine at Mount Sinai Morningside, New York
AI serves as an additional set of eyes for radiologists, enhancing detection by flagging lung nodules that may require further evaluation. This AI-driven approach may aid in identifying more nodules which we hope supports patient care and enables us to evaluate the broader impact of medical imaging AI. The clinical trial will evaluate how many patients require follow-up CT scans, biopsies, and how many more lung cancer cases are diagnosed earlier using AI. The hope is that this clinical trial will not only advance early detection but also drive meaningful transformation in lung cancer surveillance
Amit Gupta
Cardiothoracic Radiologist and Modality Director of Diagnostic Radiography at University Hospitals Cleveland Medical Center
The advantages of LLM-based AI solutions
NLP
Rule-first Processing
Treats all nodules the same without anatomy, risk, or context.
Relies on predefined rules & keywords lists
Finds the word, not the meaning
Scans reports for exact matches
Triggers in any occurrence of “nodule”
Ignores critical context
- Synonyms & reporting variations confuse rules
- All nodules treated the same
Leads to poor outcomes
- 30–40% overcalling → alert fatigue
- 10–20% undercalling → misses
LLM
Reason-first Intelligence
Extracts context to assess true risk per nodule.
Integrates multiple data sources
Prior imaging, history, risk factor, report text
Understands full clinical context
Analyzes findings in relation to the specific patient
Reasoning like a trained junior doctor
- Handles synonyms, nuance, report styles
- Produces logic-based clinical insights
Delivers intelligent outcomes
- Accurate triage & risk assessment
- < 5% error rate with minimal false positive
Products
qLC Suite
Lung Cancer Suite
- Detect early-stage lung cancers on chest X-rays and stratify malignancy risk on CT to guide treatment decisions
- Coordinate follow-up and manage at-risk patients with qTrack, enabling timely intervention and streamlined care
qER Suite
Emergency Suite
- Detect emergent findings like ICH, LVO, PE, PTX and fractures on CT and X-ray
- Support rapid triage and faster intervention across emergency care pathways
qLC Suite | qER Suite
qTrack
- Unified solution for radiologists to access AI findings, clinical context, and follow-up tools, all within a single, contextual interface
- Built for real-world workflows: trigger alerts for incidental and emergent findings, streamline communication, and close the loop on care
Reach out to us
News
Impact & Evidence
Reimbursement
Reimbursement for AI-enabled lung cancer and neurocritical care pathways is evolving. Qure’s products within the lung cancer and neuro pathways are billable under CMS-issued CPT codes (such as 0721T, 0727T), allowing hospitals to establish a stable revenue model while optimally utilizing AI solutions to improve accurate and faster diagnostics. Qure works with revenue-cycle teams to align documentation, coding, and payer engagement within existing imaging and follow-up workflows. Some partners report success under established routes; others are assessing emerging options as coverage varies by payer type. Please consult local medical-necessity and documentation policies before billing and prior authorization.
For more information please write to us at partner@qure.ai
