For millions of people with epilepsy and movement disorders such as Parkinson’s disease, electrical stimulation of the brain already is widening treatment possibilities. In the future, electrical stimulation may help people with psychiatric illness and direct brain injuries, such as stroke.
Scientists at the Icahn School of Medicine at Mount Sinai described the creation of a new, automated, artificial intelligence-based algorithm that can learn to read patient data from electronic health records. In a side-by-side comparison, they showed that their method, called Phe2vec (FEE-to-vek), accurately identified patients with certain diseases as well as the traditional, “gold-standard” method, which requires much more manual labor to develop and perform
New technology, using robotics and AI, is supercharging efforts to protect grape crops and will soon be available to researchers nationwide working on a wide array of plant and animal research.
The American College of Radiology® Data Science Institute® (ACR DSI) and the American Academy of Ophthalmology today announced a collaboration that will expand ACR DSI’s groundbreaking AI-LAB™ platform to include eye care.
New Columbia Engineering study unveils a computer vision technique for giving machines a more intuitive sense for what will happen next by leveraging higher-level associations between people, animals, and objects.“Our algorithm is a step toward machines being able to make better predictions about human behavior, and thus better coordinate their actions with ours,” said Computer Science Professor Carl Vondrick. “Our results open a number of possibilities for human-robot collaboration, autonomous vehicles, and assistive technology.”
Israeli scientists have demonstrated a novel means of diagnosing tuberculosis by means of a sticker patch that catches compounds released by the skin. Using an artificial intelligence (AI) analysis of these compounds, the scientists were able to provide a quick, non-invasive diagnosis.
The Mount Sinai Hospital is ranked No. 1 in the New York City metropolitan area and No. 4 globally among the most technologically advanced health care institutions on Newsweek’s list of “The World’s Best Smart Hospitals 2021.”
University Hospitals in Cleveland is the global pioneer in full clinical adoption of GE Healthcare’s new Critical Care Suite 2.0, the world’s first on-device artificial intelligence program helping to assess endotracheal tube placement.
“Gun violence in this country is an epidemic, and it’s an international embarrassment,” President Biden recently said. At least 45 mass shootings have occurred in America in the last month, according to reports. In the same time period, news of…
Mayo Clinic announced a new technology platform initiative to deliver the next generation of clinical decision support tools, diagnostic insights and care recommendations to help clinicians make faster and more accurate diagnoses and provide truly continuous care to patients. The Remote Diagnostics and Management Platform (RDMP) connects data with innovative new artificial intelligence (AI) algorithms and augments human decision-making within existing clinical workflows. RDMP enables “event-driven medicine,” providing insights in the right context, at the right time.
Researchers at the Bloomberg Kimmel Institute for Caner Immunotherapy at the Johns Hopkins Kimmel Cancer Center have developed DeepTCR, a software package that employs deep-learning algorithms to analyze T-cell receptor (TCR) sequencing data. T-cell receptors are found on the surface of immune T cells. These receptors bind to certain antigens, or proteins, found on abnormal cells, such as cancer cells and cells infected with a virus or bacteria, to guide the T cells to attack and destroy the affected cells.
Unbound Medicine® today announced a major upgrade to their digital publishing platform. Unbound developed Unbound Intelligence™‒ exclusive artificial intelligence and machine learning tools to help clinicians keep up to date with current research, as well as discover and fill knowledge gaps.
Cats and dogs. Huskies and wolves. While AI research sometimes seems dominated by talk about animals, the discussions are critical for understanding AI decisions. This “explainable AI” research is critical for many domains, including the detection of nuclear explosions or the movement of materials that endanger the nation’s security.
Researchers at The University of South Australia have successfully tested a system that can monitor soil moisture using just a standard camera and an AI algorithm. The system holds huge potential as a simple, affordable solution for smart agriculture, allowing for automated, precision irrigation.
New computer simulation forecasts a surprisingly optimistic heat load for future fusion facilities designed to harvest on Earth the fusion that powers the sun and stars to generate electricity.
Researchers from Mayo Clinic and AliveCor Inc. have been using artificial intelligence (AI) to develop a mobile device that can identify certain patients at risk of sudden cardiac death. This research has yielded a breakthrough in determining the health of the electrical recharging system in a patient’s heart. The researchers determined that a smartphone-enabled mobile EKG device can rapidly and accurately determine a patient’s QTc, thereby identifying patients at risk of sudden cardiac death from congenital long QT syndrome (LQTS) or drug-induced QT prolongation.
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.
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.
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.
Experts 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.
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.
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.
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.
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.
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.
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.
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.
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.
Artificial intelligence, or “supervised machine learning,” could help identify which well-appearing infants with fever, who are 60 days old or younger, are at low risk for a serious bacterial infection, according to a study published in Pediatrics. Accurate risk determination could reduce unnecessary lumbar puncture, antibiotics and hospitalizations for these infants, as well as decreasing parental anxiety.
The overwhelming ‘Whiteness’ of artificial intelligence – from stock images and cinematic robots to the dialects of virtual assistants – removes people of colour from the way humanity thinks about its technology-enhanced future, according to Cambridge researchers.
The project could pave the way for small, mobile quantum networks and possibly lead to unbreakable, secure communication systems, quantum computers and enhanced radar.
Sedentary behaviours, poor sleep and questionable food choices are major contributors of chronic disease, including diabetes, anxiety, heart disease and many cancers. But what if we could prevent these through the power of smart technologies?
Johns Hopkins Carey Business School Associate Professor Jim Kyung-Soo Liew leads a team that has created an online map showing the locations of coronavirus testing stations throughout the United States.
Medical physicists at the Mayo Clinic have just made a unique library of computed tomography (CT) data publicly available so that imaging researchers can study, develop, validate, and optimize algorithms and enhance imaging hardware to produce peak-quality CT images using low radiation doses.
On the 50th anniversary of Earth Day, SAS and the International Institute for Applied Systems Analysis join forces to transform crowdsourced knowledge into actionable intelligence to help protect the planet.
Bioengineers have combined standard microscopy, infrared light, and artificial intelligence to assemble digital biopsies that identify important molecular characteristics of cancer biopsy samples.
Proteins are the building blocks of life and scientists have long studied how to improve them or design new ones. Traditionally, new proteins are created by mimicking existing proteins or manually editing their amino acids. This process is time-consuming, and it is difficult to predict the impact of changing an amino acid. In APL Bioengineering, researchers explore how to create new proteins by using machine learning to translate protein structures into musical scores, presenting an unusual way to translate physics concepts across domains.
A new study by Carey Business School researchers notes that some expert medical diagnosticians may order fewer patient tests as a way to indicate a high level of competence to their peers. They do so despite an increase in diagnostic techniques that can assess patient condition more accurately than former methods.
The new report is designed to be a comprehensive reference for organizational leaders, health care professionals, data analysts, model developers and those who are working to integrate machine learning into health care, said Vanderbilt University Medical Center’s Michael Matheny, MD, MS, MPH, Associate Professor in the Department of Biomedical Informatics, and co-editor of AI in Healthcare: The Hope, The Hype, The Promise, The Peril.
The University of California, Santa Cruz, has established a new master’s (M.S.) degree program in Natural Language Processing (NLP), offered from the UCSC Silicon Valley Campus in Santa Clara. This innovative professional degree program will give students a strong background in the advanced computational technologies used to process and analyze the natural language that humans speak and write.
How do you integrate ethics, policy, and practicality into the design of revolutionary robotics and artificial intelligence systems? Researchers Kagan Tumer and Tom Dietterich are collaborating to find out as they help lead the Oregon State Collaborative Robotics and Intelligent Systems Institute.
DHS S&T awarded $147,413 to KickView Corporation to adapt their multi-sensor artificial intelligent (AI) software platform to provide real-time data analysis of passenger flow in the international customs processing areas of airports.
Mount Sinai Health System has earned the 2019 College of Healthcare Information Management Executives (CHIME) Most Wired recognition according to survey results released this month.
Dr. Benji Maruyama is a Principal Materials Research Engineer in the Air Force Research Laboratory, Materials & Manufacturing Directorate. He is the Leader of the Flexible Materials and Processes Research Team, and leads research on the synthesis and processing science…
Six new nuclear reactor technologies are planned to commercially deploy between 2030 and 2040. ORNL’s Weiju Ren heads a project managing structural materials information. This conversation explores challenges and opportunities in sharing nuclear materials knowledge internationally.
AI-assisted training will make surgery safer A team led by Dr. Rolando Del Maestro is playing a major role in perfecting an advanced neurosurgical simulator. “There is no way in the next five years that medical students going into neurosurgery…