Study develops a ConvLSTM model that accurately predicts patient deterioration based on facial expressions, achieving 99.89% accuracy, with potential to improve early detection in healthcare settings.
“These results confirm that computerized tongue analysis is a secure, efficient, user-friendly and affordable method for disease screening that backs up modern methods with a centuries-old practice,”
This technology could be aah-mazing!
Researchers in Iraq and Australia say they have developed a computer algorithm that can analyze the color of a person’s tongue to detect their medical condition in real time — with 98% accuracy.
Continue reading “AI model 98% accurate in detecting diseases — just by looking at your tongue” »
Microsoft patches critical flaws in Azure Health Bot Service that could expose patient data. Researchers detail vulnerabilities and their potential im.
Preclinical study investigates neuron-targeted partial cellular reprogramming in the hippocampus to mitigate age-related cognitive impairments.
A new publication has discovered ways to reduce the toxicity of graphene oxide (GO), an ultra-thin sheet of nanomaterial derived from graphite, laying the groundwork to use it as a drug delivery system.
Professor Khuloud Al-Jamal, who led the study, said: “Researchers have been incredibly excited in the potential medical applications of graphene since experiments into the nanomaterial were recognised with the Nobel Prize in Physics in 2010. However, concerns around toxicity have remained a consistent obstacle.”
Graphene oxide (GO) is an ultra-thin sheet derived from graphite. It is similar to pencil lead but includes attached oxygen atoms, making it compatible with water. Its unique physical and chemical properties mean it has a high capacity for carrying antibiotics and anticancer drugs, among others, as well as targeting specific cells, making it a potentially effective drug delivery system.
Nearly invisible, seaweed-based electronic skin precisely monitors pulse pressure and temperature, rivaling medical equipment in accuracy with its innovative bioelectronic design.
Completely changing your diet can be hard, so a longevity expert and doctor added foods including olive oil to his diet for the healthy aging benefits.
While new technologies, including those powered by artificial intelligence, provide innovative solutions to a steadily growing range of problems, these tools are only as good as the data they’re trained on. In the world of molecular biology, getting high-quality data from tiny biological systems while they’re in motion – a critical step for building next-gen tools – is something like trying to take a clear picture of a spinning propeller. Just as you need precise equipment and conditions to photograph the propeller clearly, researchers need advanced techniques and careful calculations to measure the movement of molecules accurately.
Matthew Lew, associate professor in the Preston M. Green Department of Electrical & Systems Engineering in the McKelvey School of Engineering at Washington University in St. Louis, builds new imaging technologies to unravel the intricate workings of life at the nanoscale. Though they’re incredibly tiny – 1,000 to 100,000 times smaller than a human hair – nanoscale biomolecules like proteins and DNA strands are fundamental to virtually all biological processes.
Scientists rely on ever-advancing microscopy methods to gain insights into these systems work. Traditionally, these methods have relied on simplifying assumptions that overlook some complexities of molecular behavior, which can be wobbly and asymmetric. A new theoretical framework developed by Lew, however, is set to shake up how scientists measure and interpret wobbly molecular motion.
Innovation At The Frontiers Of Aesthetic And Regenerative Medicine — Prof. Dr. Alan Widgerow — Division Chief, Center for Tissue Engineering, UCIrvine — Chief Scientific Officer, Galderma.
Prof. Dr. Alan Widgerow, MBBCh, FCS, MMed, FACS, is Division Chief, Research, Center for Tissue Engineering (https://sites.uci.edu/ctelab/team/) and Adjunct Professor Plastic Surgery, Dept of Plastic Surgery, University of California, Irvine (https://faculty.uci.edu/profile/?facu…) and Chief Scientific Officer and Head of Skin Science Center of Innovation at Galderma (https://www.galderma.com/).
A newly published study by Sheba Medical Center, Israel’s largest and internationally ranked hospital, shows that AI analysis of medical records as patients are admitted to the ER can accurately identify those at high risk of pulmonary embolism (PE).
A pulmonary embolism is a sudden blockage in an artery in the lung caused by a blood clot, most commonly due to a dislodged clot in the leg. They are normally diagnosed during a CT scan.
Using machine learning, the researchers trained an algorithm to detect a pulmonary embolism before a patient was hospitalized, based on existing medical records.
