Using routine medical CT imaging already available in the system
Can help identify more patients with early chronic conditions
Can help identify patients with asymptomatic undetected chronic disease earlier in their patient journey
Can help clinicians to identify patients at risk and improve patient care
Nanox.AI solutions provide the ability to use AI to highlight and help identify patients with asymptomatic undetected chronic disease, initiating earlier diagnosis and preventative management
FDA Cleared* | CE
AI algorithm that automatically detects coronary artery calcification (CAC) to help identify patients at risk of coronary artery disease without a need for discrete imaging.
Coronary artery disease (CAD)
Nanox.AI HealthCCSng assesses
CAC levels, a core predictor of future cardiac events, from a health care organization’s certain pre-existing routine chest CT scans, not just those performed for CAD assessment
CAC is a key metric that can enable early intervention,
as patients in the highest CAC category are over 6x more
likely to suffer a cardiac event [1]
Nanox.AI HealthCCSng device uses AI processing to analyze organizations’ throughput of non-contrast, non-gated chest CT scans to quantify CAC, appending CAC level categories and provide the clinicians insights on potential patients at risk
Nanox.AI HealthCCSng device uses AI processing to analyze organizations’ throughput of non-contrast, non-gated chest CT scans to quantify CAC, appending CAC level categories and provide the clinicians insights on potential patients at risk
1. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030975/
* FDA 510(k) Cleared - K210085
FDA Cleared *
Algorithm that automatically detects vertebral compression fractures and low bone mineral density to help identify patients at risk of musculoskeletal disease without a need for discrete imaging
Osteoporosis
Nanox.AI HealthOST assesses presence of and vertebral compression fractures (VCF) and low bone mineral density (BMD), key warning signs of osteoporosis, from a healthcare organization’s routine chest and abdominal CT scans not specifically performed for osteoporosis assessment
Nanox.AIHealthOST identification of VCFs or BMD can enable early intervention, as the World Congress on osteoporosis estimates ~66% of VCFs go undetected or unreported in osteoporosis cases, [1] which affects about 1 in 3 women and 1 in 5 men over age 50 [2]
Nanox.AI HealthOST uses AI processing to help physicians analyze organizations’ chest and abdomen CT scans that display the spine to identify VCFs and low BMD to identify patients with suspected osteoporosis.
NanoxAI HealthOST algorithm can automatically populate the VCFs and low BMD results , that can be included in the radiology report, which can then be used to help physicians make clinical care recommendations and increase early diagnosis and treatment for patients at high risk.
1. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8203169/
2. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5335887/
* FDA 510(k) Cleared -K213944
In development
AI algorithm is being developed to identify patient’s with fatty liver without a need for discrete imaging
Hepatic Steatosis, NASH
Fatty Liver (HealthFLD) solution is being designed to detect early signs of fatty liver diseases from a healthcare organization’s chest and abdomen CT scans not specifically performed for fatty liver assessment
Increase the number of patients identified with early chronic conditions
Can detect patient conditions earlier
Healthcare professionals identify patients with chronic conditions and direct patients to appropriate clinical pathways
May generate revenues for your health system with an attractive ROI model
Increases system-wide productivity by directing patients to appropriate clinical pathways
Bolstering the medical facility’s cutting-edge and innovative capabilities
May increase revenue due to higher patient retention within the medical system
Can direct at-risk patients to a clinical pathway for revenue generating medical work up
May reduce costs of chronic disease management by helping identify patients at risk earlier
Healthcare providers and payers can now benefit from AI medical imaging technology by identifying early signs of chronic disease in large populations and raising the quality of care
Nanox.AI’s medical artificial intelligence technology was designed to leverage the vast volume of existing medical images and high demand for imaging health care, a largely untapped pool of big data, to help identify early signs of chronic disease in large populations, integrating with clinical workflows of clinicians and helping to promote cost-savings for the broader health system
The ability to identify patients with subclinical chronic disease offers an opportunity to provide early intervention to patients that can substantially reduce critical events and hospitalization. Nanox.AI includes insights based on established clinical pathways. Our solutions enable primary care physicians to provide early intervention for newly diagnosed patients
Nanox.AI’s reliable cloud-based technology and seamless integration within existing workflows, is an artificial intelligence augmentative tool highlighting imaging findings with measurement that streamline the radiologists' workflow enriching their diagnostic report to include these subclinical chronic disease findings alongside the reporting that addresses the original clinical indication for the imaging. Using this tool, radiologists can be empowered to become leaders in the field of preventative healthcare
Telehealth Medicine published a pilot study from Spectrum Health that described how Nanox.AI’s fully automated software programs, including HealthOST (bone solution) and HealthCCSng (cardiac solution), can seamlessly integrate within existing workflows to highlight measurements findings that physicians can act upon
Assessment of Coronary Artery Calcification on Non-Gated Conventional CT Scans Using Artificial Intelligence Integraion
Assessment of Coronary Artery Calcification on Non-Gated Conventional CT Scans Using Artificial Intelligence Integraion
Fully-convolutional deep-learning based system for coronary calcium score prediction from non-contrast chest CT
Fully-convolutional deep-learning based system for coronary calcium score prediction from non-contrast chest CT
Fully-convolutional deep-learning based system for coronary calcium score prediction from non-contrast chest CT
Using machine learning algorithms to review computed tomography scans and assess risk for cardiovascular disease: Retrospective analysis from the National Lung Screening Trial (NLST)
Using machine learning algorithms to review computed tomography scans and assess risk for cardiovascular disease: Retrospective analysis from the National Lung Screening Trial (NLST)
Using machine learning algorithms to review computed tomography scans and assess risk for cardiovascular disease: Retrospective analysis from the National Lung Screening Trial (NLST)
Lung Cancer Screening programs can achieve greater clinical benefit by leveraging the Nanox.AI CAC measurement tool
Lung Cancer Screening programs can achieve greater clinical benefit by leveraging the Nanox.AI CAC measurement tool
Lung Cancer Screening programs can achieve greater clinical benefit by leveraging the Nanox.AI CAC measurement tool
The Value – Leverage AI to go beyond the standard read; HealthCCSng cardiac solution detects more patients eligible for preventive treatment
The Value – Leverage AI to go beyond the standard read; HealthCCSng cardiac solution detects more patients eligible for preventive treatment
Closing the Loop in AI, EMR, and Provider Partnerships: The Key to Improved Population Health Management?
Closing the Loop in AI, EMR, and Provider Partnerships: The Key to Improved Population Health Management?
Closing the Loop in AI, EMR, and Provider Partnerships: The Key to Improved Population Health Management?
Compression Fractures Detection on CT
Compression Fractures Detection on CT
Compression fractures detection on CT
Automated opportunistic osteoporotic fracture risk assessment using computed tomography scans to aid in FRAX underutilization
Automated opportunistic osteoporotic fracture risk assessment using computed tomography scans to aid in FRAX underutilization
Automated opportunistic osteoporotic fracture risk assessment using computed tomography scans to aid in FRAX underutilization
NanoxAI Bone tool increased the number of detected patients and promoted preventive treatment
NanoxAI Bone tool increased the number of detected patients and promoted preventive treatment
NanoxAI Bone tool increased the number of detected patients and promoted preventive treatment
Vertebral fractures are often undiagnosed and missed by FLSs. We have demonstrated the impact of an AI-enabled vertebral fracture FLS pathway using existing CT images on anti-osteoporosis treatment adherence
Vertebral fractures are often undiagnosed and missed by FLSs. We have demonstrated the impact of an AI-enabled vertebral fracture FLS pathway using existing CT images on anti-osteoporosis treatment adherence
In the study population - NanoxAI Bone tool helped detect more patients at-risk of osteoporosis when comparing to standard of care (FRAX)
In the study population - NanoxAI Bone tool helped detect more patients at-risk of osteoporosis when comparing to standard of care (FRAX)
A recent study suggests high clinical and economic efficacy for opportunistic screening using the AI tools. Nanox.AI solutions can enable and simplify cost savings by helping detect and report opportunistic findings related to chronic diseases
A recent study suggests high clinical and economic efficacy for opportunistic screening using the AI tools. Nanox.AI solutions can enable and simplify cost savings by helping detect and report opportunistic findings related to chronic diseases
A recent study suggests high clinical and economic efficacy for opportunistic screening using the AI tools. Nanox.AI solutions can enable and simplify cost savings by helping detect and report opportunistic findings related to chronic diseases
Detection of Moderate Hepatic Steatosis on Portal Venous Phase Contrast-Enhanced CT: Evaluation Using an Automated Artificial Intelligence Tool
https://www.ajronline.org/doi/abs/10.2214/AJR.23.29651
https://www.ajronline.org/doi/abs/10.2214/AJR.23.29651
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