A key symptom of COVID-19 – oxygen saturation – is now being estimated remotely from a camera, thanks to research from University of South Australia (UniSA).
Why do people learn new skills at different speeds? A medical training aid is addressing this question by blending sensory technology with psychological insight.
Scientists have used machin -learning to organize the chemical diversity found in the ever-growing databases for the popular metal-organic framework materials.
avateramedical GmbH announced the acquisition of FORWARDttc GmbH, an automation technology company with special focus on robotics hard- and software.
The Fraunhofer IBMT is developing the miniaturized ultrasound system for automated monitoring of bladder irrigation.
Researchers have developed a framework that will help data scientists and other researchers use better digital health tools for clinical purposes.
Pathologists who examined the computationally stained images could not tell them apart from traditionally stained slides.
Using machine learning, a team of Western computer scientists and biologists have identified an underlying genomic signature for 29 different COVID-19 DNA sequences.
Thanks to smart software doctors will soon be able to detect early signs of esophageal cancer in patients with so-called Barrett’s esophagus.
A software tool uses artificial intelligence to recognize cancer cells from digital pathology images — giving clinicians a powerful way of predicting patient outcomes.
Patients could soon get faster and more accurate diagnoses with new software that can automatically detect signs of diabetes, heart disease and cancer from medical images.
Researchers have created a novel 3D printing workflow that allows cardiologists to evaluate how different valve sizes will interact with each patient's unique anatomy, before the medical procedure is actually performed.
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.
Researcher have developed algorithms that analyze patients‘ imaging data and calculate surgical risks. This makes liver cancer surgery safer and easier to plan.