EMPOWERING HEALTHCARE DIAGNOSIS WITH ARTIFICIAL INTELLIGENCE
Current Status
testing for application ongoing
Problem or Opportunity
Chest X-rays are currently the best available method for diagnosing different lung associated diseases like hernia, pneumonia, fibrosis, edema, emphysema, cardiomegaly, pleural thickening, consolidation, pneumothorax, mass, nodule, atelectasis, effusion and infiltrations. Our application can detect diagnosis of each of these conditions faster than an average processing time from a radiological laboratory.
Solution (product or service)
Chest X-ray exam is one of the most frequent and cost-effective medical imaging examinations. However clinical diagnosis of chest X-ray can be challenging, and sometimes believed to be harder than diagnosis via chest CT imaging. Even some promising work have been reported in the past to achieve a clinically relevant computer-aided detection and diagnosis (CAD) in real world medical sites on all data settings of chest X-rays is still very difficult. Our vision is to decrease the diagnosis burden with improving diagnosis accuracies.
