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.
Researchers have developed a new AI platform that detects COVID-19 by analyzing X-ray images of the lungs.
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.
Researchers have developed a predictive artificial intelligence model that can tell the difference between healthy patients, those who are ill with pneumonia and those who have COVID-19, from chest X-rays.
behold.ai has been issued with a CE Mark Class lla certification in the UK and EU for its AI-based technology that can diagnose chest X-rays as ‘normal’.
Researchers at the University of Stuttgart have developed a miniature laboratory the size of the tip of a needle.
Researchers have designed a novel approach to use deep learning to better understand how proteins interact in the body.
A computer algorithm has been shown to be as effective as human radiologists in spotting breast cancer from x-ray images.
Researchers refined application of terahertz radiation to promote the analysis of multi-layered tissues for medical purposes and be used for wound treatment.
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.
Spine surgery: A new robotic technology increases the safety and precision of spinal fusion surgeries while reducing the time needed for the procedure.
Researchers have created new AI software that can identify cardiac rhythm devices in x-rays more accurately and quickly than current methods.
Researchers have created new machine learning software that can forecast the survival rates and response to treatments of patients with ovarian cancer.
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.
A "Hive Mind" of doctors, moderated by AI algorithms, makes more accurate diagnoses than the doctors or machine learning alone, according to a new study from Stanford and Unanimous AI.
Researchers have engineered yeast "microbreweries" to help hospital lab workers better track their daily radiation exposure, enabling a faster assessment of tissue damage that could lead to cancer.
Researchers from the University of Toronto use machine learning to create computer generated X-rays that augment AI training sets, which could improve the speed and accuracy of medical diagnostics.
Researchers developed a new holographic method called in-flight holography. With this method, they were able to demonstrate the first X-ray holograms of nano-sized viruses that were not attached to any surface.
