Southampton researchers developed an AI that surpassed radiologists in detecting hard-to-see airway obstructions on chest CT scans.
Key Details
- 1AI tool developed at University of Southampton detects radiolucent airway foreign bodies on chest CT.
- 2In study of 70 CT scans (14 positive for radiolucent FBA), radiologists detected 36% of cases; AI detected 71%.
- 3Radiologists had 100% precision but lower recall, while AI had 77% precision (some false positives).
- 4AI's F1 score (74%) exceeded that of radiologists (53%).
- 5Model tested on over 400 patient scans across three cohorts; aims to support, not replace, radiologists.
- 6Study published in npj Digital Medicine; research collaboration included UK and China.
Why It Matters
AI support can significantly improve detection of subtle, life-threatening foreign bodies in airways that are often missed on standard imaging, enhancing patient safety and outcomes. This work highlights the growing role of AI as an assistive tool in challenging radiological diagnoses.
Source
EurekAlert
Related News
•EurekAlert
AI-Driven CT Imaging Predicts Cardiac Events in Large UK Cohort
An AI tool analyzing CCTA images can predict future cardiovascular events and death in patients with suspected stable coronary artery disease.
•EurekAlert
AI Multimodal Models Improve Breast Cancer Recurrence Risk Prediction
Initial results from an ECOG-ACRIN and Caris Life Sciences collaboration show AI-driven multimodal models can more accurately predict recurrence risk in early-stage breast cancer.
•EurekAlert
AI Tool from UCLA Targets Undiagnosed Alzheimer's and Diagnostic Disparity
UCLA researchers developed an AI model using EHR data to better detect undiagnosed Alzheimer's disease, especially in underrepresented groups.