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AI analysis for Chest x-ray
AI analysis for Mammography
AI analysis for Tissue Slides
Chest radiography is one of the most basic and fundamental diagnostic test used in medicine, accounting for 25% of the annual total numbers of diagnostic imaging procedures.1 It has been shown that radiologic information changed clinical practice in more than 60% of those who received chest radiography.2,3 Unfortunately, miss rates for proper interpretation of chest radiographs go as high as 30% even for experts,4,5 leading to increased mortality from treatable diseases.6 Moreover, interpretive performance of chest radiographs differ significantly between specialists and non-specialists, upto 30%.7-9 Among the various diseases detected or diagnosed through chest radiography, lung cancer (nodule/mass), tuberculosis, pneumonia (consolidation), and pneumothorax are among the most common and major diseases.
Developed using Lunit’s cutting-edge deep learning technology,10 Lunit INSIGHT CXR-MCA accurately detects lung nodule/mass, consolidation, and pneumothorax in the form of diagnostic support tool. The AI solution generates (1) location information of detected lesions in the form of heatmaps and (2) abnormality scores reflecting the probability that the detected lesion is abnormal. The solution is indicated to be directly involved in the primary interpretation process of radiologists or clinicians.
Primary value proposition
- Prevent difficult cases of major chest abnormalities from being missed upon reading chest radiographs.
- Help physicians make early diagnosis of major chest abnormalities in chest radiographs.
- Enable non-specialists to perform at specialist level in detecting major chest abnormalities in chest radiographs.
Training & Validation
- Trained with a large-scale (>200,000 cases), high-quality (clinically/CT-proven cases) training set.
- Demonstrated to perform at a standalone accuracy of 98-99% in ROC AUC.11
- Clinically validated to significantly improve the interpretive capabilities of clinicians and radiologists upto 20%.
- Currently in preparation for regulatory approval in various markets worldwide, including FDA, CE, MFDS.
CASE #1. A small nodule, diagnosed as lung cancer, is properly detected in the right middle lung field, with an abnormality score of 94%.
CASE #2. Subtle focal consolidation, diagnosed as pneumonia, is properly detected in the right lower lung field, with an abnormality score of 81%.
CASE #3. Subtle pneumothorax is properly detected in the left apex, with an abnormality score of 57%.
CASE #4. Focal consolidation, diagnosed as tuberculosis, is properly detected in the right apex hidden behind the clavicle, with an abnormality score of 72%.