X-ray Screening
X-ray Screening Care Mentor AI
Designed for the analysis of chest X-ray in straight view and the subsequent interpretation.
Based on the results of the analysis of the diagnostic image, the CMAI provides the user with a protocol containing the classification of X-ray images into the categories "with pathological changes identified" and "without pathological changes".

The users (consumers) of the medical device are medical doctors and healthcare providers.
Advantages of use for healthcare professionals:
• Increased screening speed + prioritization of cases with identified pathology, including socially significant ones like oncology, pneumonia and tuberculosis.
• Getting a second opinion
• Reduce the risks of medical errors
• Improving workflow and quality of radiology departments
Clinical side

CMAI screening system makes X-ray images triage based on more than 8 groups of pathological changes:

- Focal changes and nodules (characteristic of cancer and tuberculosis)
- Consolidation (characteristic of pneumonia, tuberculosis)
- Lung roots changes
- Pulmonary and vascular pattern dieorders (characteristic of pneumosclerosis / pneumofibrosis)
- Emphysema, expansion of the median shadow (characteristic of pathology of the heart and mediastinum)
- Pleural effusion
- Bone damage (fractures, scoliosis)
Metrics:
86%

Accuracy is above the target percentage, demanded
by regulating institutions:
7 seconds

Time spent to analyze PNG/JPEG images
15 seconds

Time spent to analyze DICOM images
800 000 images

Training Database
0,86

Sensitivity
0,92

Specificity
0,91

Accuracy
0,93

ROC AUC
Scientific works
«Diagnostic Imaging Europe»
FEB/MARCH, 2020

Promising AI-based approach to lung pathology and foreign body detection in the chest
By Dr. D Blinov, Dr. E Zhukov, Dr. V Leontiev & Dr. E Blinova

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«Imaging in Medicine»
№5, 2019

Advanced neural network solution for detection of lung pathology and foreign body on chest plain radiographs

By Lilian Nitris, Evgenii Zhukov, Dmitry Blinov, Pavel Gavrilov, Ekaterina Blinova & Alina Lobishcheva

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«Imaging in Medicine»
№5, 2019

Advanced neural network solution for detection of lung pathology and foreign body on chest plain radiographs

By Lilian Nitris, Evgenii Zhukov, Dmitry Blinov, Pavel Gavrilov, Ekaterina Blinova & Alina Lobishcheva

Read the article