EMPOWERING HEALTHCARE DIAGNOSIS WITH ARTIFICIAL INTELLIGENCE
OUR PATENT PENDING* TECHNOLOGY
01 / FAST
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.
02 / SECURE
The users private radiological data is analyzed on a secure cloud platform.
03 / EASY
< 1 Minute Per Image
ChestAi was started with computer scientists and geneticists at Yale university with a common motivation of providing a free and open source platform for rapid and robust diagnosis of pathologies identified by radiological examinations.
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.
With approximately 2 billion procedures per year, chest X-rays are the most common imaging examination tool used in practice, critical for screening, diagnosis, and management of lung diseases. However, an estimated two thirds of the global population lack access to radiology diagnostics. With automation at the level of experts, we hope that this technology can improve healthcare delivery and increase access to medical imaging expertise in parts of the world where access to skilled radiologists is limited.