Chest X-ray and Fluorography
Detects signs of tuberculosis, pneumonia, lung cancer, suppurative and necrotic conditions. Defines pleural effusion, pneumothorax, rib fractures, and cardiomegaly
500+ medical institutions
Have implemented the “Third Opinion” AI service
SaMD
Class III medical device registration certificate
8 regions
Deployed the AI service for X-ray and fluorography analysis
Unified register of russian software
Included by Order No. 983 of the Ministry of Digital Development dated 20.09.2021
AI Algorithm detects and describes
Physician receives a pre-filled report
After AI processing
Example Report
Lungs: No focal or infiltrative changes detected
Bones: Consolidated rib fracture detected
Heart: Mediastinum enlargement. CTI = 0.6
Conclusion: No focal or infiltrative changes detected

Conclusion
No focal or infiltrative changes detected
Diagnosis: Cardiomegaly
97% Sensitivity
Proven by independent testing
700,000+ Studies
Processed by the “Third Opinion” AI service
< 1 Minute
Average processing time per study
Use case scenarios
Retrospective analysis
Processes study archives and detects missed pathologies. Provides analytics at the facility or regional level
Normal case sorting
Separates "normal" from "pathology," prioritizes studies with deviations, optimizes the specialist's workflow, and helps focus on suspicious signs
Analyzes the study, highlights pathological signs, and generates a pre-filled report
Radiologist assistant
Calculate the economic benefits of implementing an AI service for your organization
AI for Higher-Quality Care
03
Assesses study quality and reports technical defects
02
Automatically generates reports for “normal” studies
01
Reduces report preparation time by up to 30%
DICOM Image
AI processes the study
Integration Workflow
Returns
a secondary DICOM series with AI-visualization
a pre-filled report
Workstation
Device
Third Opinion
Возвращается дополнительная серия с ИИ-визуализацией и предварительно заполненный протокол
PACS
Transforming healthcare with partners
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FAQ
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Operations are carried out with grant support from the Skolkovo Foundation
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