Intended Use

Software workflow tool designed to aid the clinical assessment of adult chest X-ray cases with features suggestive of pleural effusion and pneumoperitoneum in the medical care environment. It analyzes cases using an AI algorithm to identify findings and provides case-level output to PACS or RIS for worklist prioritization or triage.

Technology

The device uses a deep learning convolutional neural network AI algorithm trained on diverse chest X-ray datasets to identify pleural effusion and pneumoperitoneum. It integrates with image and order management systems like PACS/RIS to automatically analyze studies and notify for triage prioritization. Ground truth for training and validation was established by board-certified radiologists.

Performance

Standalone performance was validated on 1269 independent chest X-rays showing high accuracy (AUC ~0.98 for pleural effusion and 0.97 for pneumoperitoneum) with strong sensitivity and specificity values across operating points. Triage effectiveness showed average turn-around time under 30 seconds. These results demonstrate safety, effectiveness, and substantial equivalence to a predicate device.

Predicate Devices

No predicate devices specified

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