Trained to see patterns by analyzing thousands of chest X-rays, a computer program predicted with up to 80 percent accuracy which COVID-19 patients would develop life-threatening complications within four days.
By using 3D aerosol jet-printing to put perovskites on graphene, scientists have made X-ray detectors with record sensitivity that can greatly improve the efficiency and reduce the cost.
Two surgeon tested a device that, when attached to everyday eyeglasses, can display fluoroscopic images used for surgical guidance directly to the surgeon.
Students at Cranfield University have designed computer models that can identify COVID-19 in X-rays.
Ensembles created using models submitted to the RSNA Pediatric Bone Age Machine Learning Challenge convincingly outperformed single-model prediction of bone age.
Radiologists assisted by deep learning based software were better able to detect malignant lung cancers on chest X-rays.
Researchers have created new AI software that can identify cardiac rhythm devices in x-rays more accurately and quickly than current methods.
In a matter of seconds, a new algorithm read chest X-rays for 14 pathologies, performing as well as radiologists in most cases, a Stanford-led study says.