news, journals and articles from all over the world.
Researchers at the Center for Computational Imaging and Personalized Diagnostics (CCIPD) at Case Western Reserve University have preliminarily validated an artificial intelligence (AI) tool to predict how likely the disease is to recur following surgical treatment for prostate cancer.
Read moreStethoscopes are a ubiquitous and cost-effective tool for medical diagnosis, but they open the door to subjectivity and can experience high levels of environmental noise. This makes it difficult to properly diagnose lung abnormalities, like COVID-19, by listening to sounds from the body. James West, at Johns Hopkins University, has been developing a digital stethoscope equipped with artificial intelligence for accurate lung diagnoses. He will discuss its opportunities and obstacles at the 179th ASA Meeting.
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Researchers from multiple institutions in North America have developed a fully automated, deep-learning (DL), artificial-intelligence clinical tool that can measure the volume of cerebral ventricles on magnetic resonance images (MRIs) in children within about 25 minutes.
Read moreExperts trained a computer to tell which skin cancer patients may benefit from drugs that keep tumors from shutting down the immune system’s attack on them, a new study finds.
Read moreMount Sinai researchers have developed machine learning models that predict the likelihood of critical events and mortality in COVID-19 patients within clinically relevant time windows.
Read moreNew research presented at ACR Convergence, the American College of Rheumatology’s annual meeting, shows that an artificial intelligence-based analysis model enables accurate detection of definite radiographic sacroiliitis in people with axial spondyloarthritis, an advance that could be useful for both diagnosis in the clinic and classification of patients for inclusion in clinical trials.
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An international research team led by PNNL has published a vision for electron microscopy infused with the latest advances in data science and artificial intelligence. Writing a commentary in Nature Materials, the team proposes a highly integrated, autonomous, and data-driven microscopy architecture to address challenges in energy storage, quantum information science, and materials design.
Read moreTrials include a model to create custom breast implants, a smarter method to recommend biopsy, a novel approach to preserve sensation in implant-based breast reconstruction, and a new clinical trial investigating a modified herpes virus as a tactic to trigger immune response.
Read moreResearchers in the Perelman School of Medicine at the University of Pennsylvania were awarded a $3.2 million grant from the NIH to enhance research for improving heart transplant outcomes for patients. The four-year grant will fund a project exploring the use of AI-driven analysis to determine the likelihood of cardiac patients accepting or rejecting a new heart.
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A new, machine-learning based approach could help doctors to separate aggressive stage 0 breast cancer from non-aggressive forms, sparing some women unnecessary mastectomies.
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The PNNL-developed VOLTTRON™ software platform’s advancement has benefited from a community-driven approach. The technology has been used in buildings nationwide, including most recently on a university campus.
Read moreTodd Mockler, PhD, will co-lead a research team applying AI approaches to extract plant phenotypes, from sensor data sets in order to accelerate crop improvement, with a focus on enhancing nitrogen and water use efficiency in major row crops such as corn and soy.
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