Scientists have developed a brain-computer interface allowing an individual to control a robotic arm with only their neural signals, without the need for invasive brain implants.
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Tool allowing radiologists to interact with AI imaging data receives FDA first-of-kind determination
A system that compiles artificial intelligence-generated imaging data into one place for radiologist analysis has been determined ready for commercialization by the FDA, according to Foster City, Calif.-based TeraRecon, a developer of digital radiology solutions.
Researchers from Verily, Alphabet's life sciences arm, developed a deep learning algorithm that can identify diabetic retinopathy with equal or better accuracy than that of trained human experts, according to a study published this month in JAMA Ophthalmology.
Commercially available smartphones and smart speakers could be trained to recognize breathing sounds indicative of cardiac arrest, then call for help, according to a proof-of-concept study published June 19 in npj Digital Medicine.
An IBM algorithm combining machine and deep learning to analyze health records and mammograms was able to predict the development of breast cancer up to 12 months before its onset with nearly 90 percent accuracy, according to a study published…
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Mount Sinai Health System has tapped Burlington, N.C.-based LabCorp to lead the integration of Philips' IntelliSite Pathology Solution into the New York City-based health system's hospitals.
Machine learning analysis of duodenal biopsy images expedited the process of imaging, diagnosing and treating gut diseases in children, according to a study published this month in JAMA Network Open.
New York City-based Mount Sinai Health System's Icahn School of Medicine announced on June 11 the launch of the Hamilton and Amabel James Center for Artificial Intelligence and Human Health, which will promote the use of AI, data science and…
When assisted by a new deep learning model, radiologists saw a marked improvement in how accurately they detected brain aneurysms from CT angiography imaging, according to a study published in JAMA Network Open this month.
Computer scientists have secured funding to develop artificial intelligence that can automatically identify signs of early-stage oral cancer using an existing screening app.