Alibaba open-sources Damo Radar model to detect 146 abdominal conditions
Alibaba Group Holding's research arm, Damo Academy, has open-sourced Damo Radar, a vision-language AI model designed to identify nearly 150 abdominal conditions from contrast-enhanced CT scans. The model covers 18 abdominal organs and can detect abnormalities such as malignant tumors. It was trained using CT scans paired with clinical reports.
Key points
- Damo Radar analyzes contrast-enhanced CT scans across 18 abdominal organs to identify 146 clinical findings.
- The model achieved an average AUC of 0.913 in nearly 40,000 real-world examinations.
- Radiologists using the model reduced diagnostic time by over 30 percent and improved missed-diagnosis prevention by 10 percent.
In nearly 40,000 real-world examinations, the model achieved an average area under the curve (AUC) of 0.913 across 146 clinical findings. In a comparative study involving 26 human radiologists, Damo Radar's average accuracy exceeded that of 23 participants. Using the model helped radiologists improve their ability to prevent missed diagnoses by 10 percent and reduced the time required by more than 30 percent, according to Damo Academy.
Model page: Damo Radar →
Alibaba open-sources AI model that can detect cancer and nearly 150 conditions
scmp.com · 18 September 2026
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