
Ping An Insurance is highlighting a new paper in Nature Communications that the company says shows that its deep-learning algorithm, AskBob Doctor AI, is effective for diagnosing pelvic and hip injuries.
Hip fractures mainly occur in elderly people and patients with major trauma, and complications of hip injuries have been associated with high mortality rates. Ping An's AI software was developed to reduce the rate of missed diagnoses and improve the comprehensiveness of detection.
In the retrospective study, a research team analyzed pelvic x-rays of 1,888 emergency room patients to evaluate the model's performance in obtaining fracture results and locations. It achieved an overall accuracy of 92.4%. Compared with general clinical diagnoses, the model substantially improves detection accuracy, according to the authors.
Ping An says the software can detect all fracture types captured on the x-rays, including hip fractures, pelvic fractures, femoral fractures, hip dislocation, and artificial joint peripheral fractures.












![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&fit=crop&h=112&q=70&w=112)






