AI Algorithm Identifies Abnormal Chest X-Rays

Image: AI algorithms match radiologists in detecting pathologies on chest X-rays and CT (Photo courtesy of Qure.ai). A clinical validation study confirms that an artificial intelligence (AI) driven algorithm can differentiate between normal and abnormal x-rays with unprecedented accuracy. Researchers at Columbia Asia Hospitals (Kuala Lumpur, Malaysia) and Qure.ai (San Mateo, CA, USA) trained a deep learning system to identify abnormal x-rays using 1.2 million x-rays and their corresponding radiology reports. Specific x-ray abnormalities included blunted costophrenic angle, calcification, cardiomegaly, cavity, consolidation, fibrosis, hilar enlargement, opacity and pleural effusion, among others. The system was tested against a three-radiologist majority analysis based on an independent, retrospectively collected, and de-identified set of 2,000 x-rays.