Artificial intelligence tool for reading MRI scans could transform prostate cancer surgery and treatment

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.

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Digital Stethoscope Uses Artificial Intelligence for Diagnosing Lung Abnormalities

Stethoscopes 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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Automatic deep-learning, artificial-intelligence clinical tool that can measure the volume of cerebral ventricles on MRIs in children

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.

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Mount Sinai Develops Machine Learning Models to Predict Critical Illness and Mortality in COVID-19 Patients

Mount 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.

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Artificial Intelligence Accurately Detects Radiographic Sacroiliitis in Axial Spondyloarthritis, Improving Diagnosis and Research

New 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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October 27, 2020 Web Feature Enabling the Data-Driven Future of Microscopy

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.

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Houston Methodist using 3D technology, artificial intelligence and more in new breast cancer research studies

Trials 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.

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Penn Researchers Receive Grant to Use AI to Improve Heart Transplant Outcomes

Researchers 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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Danforth Center Scientists Collaborate On A $20 Million Nationwide Artificial Intelligence Research Institute

Todd 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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