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Comparison of performance between artificial intelligence and radiologists in detecting abnormalities on chest X-rays
Casopis Lekaru Ceskych
|August 15, 2025
Summary
Artificial intelligence (AI) in chest X-ray analysis shows high sensitivity for detecting abnormalities, complementing radiologists. While AI excels in sensitivity, especially for less experienced doctors, human experts maintain higher specificity in diagnosis.
Area of Science:
- Radiology
- Medical Imaging
- Artificial Intelligence
Background:
- Artificial intelligence (AI) is increasingly utilized in radiology to enhance diagnostic accuracy and efficiency.
- Chest X-rays are a common imaging modality where AI shows potential for improved interpretation.
Purpose of the Study:
- To evaluate the performance of commercial AI software (Carebot AI CXR) in detecting abnormalities on chest radiographs.
- To compare AI performance against independent assessments by radiologists with varying experience levels.
Main Methods:
- A dataset of 196 anonymized chest radiographs was analyzed.
- The AI software's sensitivity and specificity were compared to 3 radiologists across 5 abnormality categories: atelectasis, consolidation, cardiac shadow enlargement, pleural effusion, and pulmonary lesions.
Main Results:
- Carebot AI CXR demonstrated high sensitivity across all evaluated abnormality categories (e.g., atelectasis 0.909, cardiac enlargement 0.889, pleural effusion 0.951).
- AI sensitivity surpassed less experienced radiologists and, in some cases, more experienced ones, albeit with a slight decrease in specificity.
- Radiologists generally achieved higher specificity, approaching 1.000 in several categories.
Conclusions:
- AI software can effectively augment the diagnostic capabilities of radiologists, particularly assisting less experienced practitioners.
- AI tools have the potential to improve the overall sensitivity of diagnoses made from chest radiographs.
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