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    AVIEW: LCSAVIEW: LCS PLUSAVIEW: COPDAVIEW: CACAVIEW: Lung TextureAVIEW: NeuroCADAVIEW: ModelerAVIEW: ResearchAVIEW: RT ACSAVIEW: Pseudonymization Server

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    • AVIEW LCS

    With the highest mortality rate, early detection is important for lung cancer treatment.

    Medical AI assists in rapid lung cancer screening
    through accurate lung nodule detection & analysis.

    AI assists rapid lung cancer
    screening through accurate
    lung nodule detection & analysis.

    MFDS • FDA • CE • PMDA • TFDA Clearance

    Detects easy to miss pulmonary nodules accurately

    Medical AI technology detects even the smallest and easy to miss nodules to human eye.

    • Sensitivity 97% / Specificity 76% for screening patients with nodules
      Pulmonary nodule detection performance 91%
    • During a comparative study (Moscow LS), our medical AI came in 2nd out of 5 participating radiologists

    Analyze & categorize pulmonary nodules quickly

    The found nodules are quickly classified according to 'Lung-RADS* ver 1.1' proposed by ACR as a lung nodule classification method.

    1. *Lung-RADS: Lung Cancer Screening CT Report And Data System
    2. *ACR: American College of Radiology

    Examine Follow-up data automatically

    By automatically matching the results of previous and follow-up examinations, changes in nodules can be immediately identified.

    The nodule volume doubling time is automatically calculated, allowing tracking and observation of key nodules convenient.

    Report results easily

    It is possible to automatically generate a lung cancer screening report without any additional work.

    It can also generate patient-facing detailed analysis reports automatically, giving back more information to the patient.

    What if a single chest CT scan could detect Big 3 disease*?

    Big 3 disease : Lung cancer, chronic obstructive pulmonary disease (COPD) and cardiovascular disease (CVD)

    • Lung Nodule Detection & Analysis
    • Emphysema Analysis
    • Coronary Artery Calcium Detection

    Evidence

    • Variability in interpretation of low-dose chest CT using computerized assessment in a nationwide lung cancer screening program: comparison of prospective reading at individual institutions and retrospective central reading

      European Radiology, 2020

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    • Implementation of the cloud-based computerized interpretation system in a nationwide lung cancer screening with low-dose CT: comparison with the conventional reading system

      European Radiology, 2020

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    • Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial

      The New England Journal of Medicine, 2020

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    • Joint Statement of the German Radiological Society and the German Respiratory Society on a Quality-Assured Early Detection Program for Lung Cancer with Low-Dose CT

      Pneumologie, 2019

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