Researchers are developing new techniques for improving 3D displays for virtual and augmented reality technologies.
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Electronic skins will play a significant role in monitoring, personalized medicine, prosthetics, and robotics.
A team of researchers at Washington University School of Medicine have developed a deep learning model that is capable of classifying a brain tumor as one of six common types using a single 3D MRI scan.
The University of Texas at San Antonio has established a wearables and AI laboratory to provide precision treatment plans to improve learning among those diagnosed with autism spectrum disorder (ASD).
X-ray vision, context-sensitive guidance, coordinator, training assistant and more: augmented reality (AR) has hit the OR.
Machine learning can be used to fill a significant gap in Canadian public health data related to ethnicity and Aboriginal status, according to research by a University of Alberta research epidemiologist.
Artificial intelligence is developing at an enormous speed and intelligent instruments will profoundly change surgery and medical interventions.
An AI algorithm is capable of diagnosing 134 skin disorders and supporting specialists by augmenting the accuracy of diagnoses and predicting treatment options.
To better leverage cancer data for research, scientists are developing an artificial intelligence-based natural language processing tool to improve information extraction from textual pathology reports.
An AI tool identified breast cancer with approximately 90 percent accuracy when combined with analysis by radiologists.
Researchers have developed a technology to help clinicians "see" and map patient pain in real-time, through special augmented reality glasses.
VR can identify early Alzheimer’s disease more accurately than ‘gold standard’ cognitive tests currently in use, suggests new research from the University of Cambridge.
A team of experts led by two University of Michigan researchers calls for attention to this shadow record.
Researcher have developed algorithms that analyze patients‘ imaging data and calculate surgical risks. This makes liver cancer surgery safer and easier to plan.