Artificial intelligence (AI) software developer Lunit is touting the results of a recent PLOS One study showing that its Insight CXR algorithm successfully detected COVID-19 pneumonia on chest radiography.
The November 24 study compared the clinical effectiveness of the algorithm with formal radiology reports using COVID-19 cases from five medical institutions in South Korea. Researchers included chest x-rays from 279 patients in the analysis, Lunit noted.
Lunit reported that Insight CXR achieved a 95.6% sensitivity and 88.7% specificity for detecting COVID-19 from the radiographs. The algorithm also showed no significant difference in area under the curve values compared with radiology reports, according to the company.
Lunit Insight CXR identifies COVID-19 pneumonia from chest radiographs. Image courtesy of Lunit.The Lunit Insight CXR algorithm has analyzed more than 6.5 million images to aid with detecting 10 major chest diseases, including lung nodules and pneumothorax. The tool has received the CE mark and is available in Europe, the Middle East, Latin America, South East Asia, Australia, and New Zealand.
![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
