Scientists Create a Labor-Saving Automated Method for Studying Electronic Health Records

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

AI Learns to Predict Human Behavior from Videos

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.”

The Mount Sinai Hospital Recognized as No. 4 on Newsweek’s World’s Best Smart Hospital 2021 List

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 First in the World to Integrate New General Electric Healthcare Imaging System into Daily Clinical Practice

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.

Mayo Clinic launches new technology platform ventures to revolutionize diagnostic medicine

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.

Software Package Enables Deeper Understanding of Cancer Immune Responses

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.

Decoding the ‘Black Box’ of AI to Tackle National Security Concerns

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.

Mayo Clinic research yields breakthrough in mobile determination of QT prolongation

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

AI Shows Promise in Accurately Identifying Infants with Low Risk of Serious Bacterial Infection

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.

Harness artificial intelligence and take control your health

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?

Composing New Proteins with Artificial Intelligence

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.

Top Doctors Limit Number of Tests They Order to Signal Diagnostic Prowess to Peers

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.

AI’s Future Potential Hinges on Consensus: NAM Report

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.

UC Santa Cruz launches new graduate program in natural language processing

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.

Artificial Intelligence/Machine Learning are rapidly changing. The materials research community is just beginning to utilize AI and ML in the research process, and it is already clear that this represents a potentially game changing development.

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…

Knowledgebase is power for nuclear reactor developers

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.