Artificial Intelligence

University College London Hospitals (UCLH) have partnered with the Alan Turing Institute to use machine learning and artificial intelligence (AI) to complete tasks currently handled by nurses and clinicians, according to The Guardian.
Researchers from the University of California, Los Angeles (UCLA) have developed an algorithm capable of accurately predicting which patients will survive a heart transplant and for how long.
AliveCor and Mayo Clinic have utilized machine learning to identify long QT syndrome (LQTS), with findings presented at the Heart Rhythm Scientific Sessions in Boston.
Researchers from the at Imperial College London and the University of Edinburgh have developed artificial intelligence (AI) software capable of detecting a common cause of dementia and stroke. Findings were published May 15 in Radiology.
Researchers from the University of Waterloo in Ontario, Canada, have developed artificial intelligence (AI) capable of using wearable-collected data to predict the onset of health problems. Findings were published Feb. 23 in the Journal of Applied Physiology.
May 15, 2018 | Analytics & Quality
The Nuffield Council on Bioethics, a British independent monitoring body, in a recent briefing note, has expressed concern regarding the ethical implications of artificial intelligence (AI) in healthcare.
Microsoft has announced a new program to fund research into using artificial intelligence (AI) to improve care for those with disabilities.
Building the infrastructure to support the accelerating adoption of AI in healthcare is the mission of Pure Storage and its FlashBlade technology, an all-flash scale-out object-based solution that can expand to petabytes of capacity. As Esteban Rubens says, infrastructure to power AI, machine learning and deep learning needs to be effortless, efficient and evergreen to ensure success today and into the future. Here’s how.
There are the believers in augmented medicine, with physicians and machines working hand in hand and improving care and patient outcomes. And there are the stalwarts who see machines taking over the tasks of mankind. Period.
Ever the visionary, Paul Chang sees AI as an asset to radiologists. As he sees it, “AI and deep learning doesn’t replace us. It frees us to do more valuable work.” The vice chair of radiology informatics at University of Chicago Medicine takes a quick look through the crystal ball at the four stand-out challenges facing radiology with the rise of AI.
To look into the future is to catch only a glimpse inside Simon Warfield’s radiology research lab at Boston Children’s Hospital. His team is pairing hyperfast imaging and deep learning to push the limits of medical imaging and artificial intelligence (AI) to identify, prevent and treat disease. He’s also eyeing ways AI will help as data sharing expands among research sites. “The research world needs to look forward to manage forward,” he says.
AI is hotter than hot in healthcare, according to AI market watcher CB Insights. Healthcare-AI funding reached $2.14 billion across 323 deals from 2012 through the second quarter of 2017—and has consistently been the top industry for AI deals.
When it comes to AI and machine learning, the regulatory trail has been blazed and the approval gates through open. The FDA has approved a couple dozen apps over the last year and a half—and the momentum is clearly building with Scott Gottlieb at the agency’s helm and recent moves to ramp up staffing to meet the demand.  
Lawrence Tanenbaum is a big believer in AI, as a tool to create better images, offer a more comprehensive view of a patient and more effectively handle imaging’s increasing volume and complexity. Bigger yet, AI is the impetus to change the way radiology and medicine are practiced across the care spectrum.
The power of artificial intelligence (AI) is enabling clinical breakthroughs that identify biomarkers without invasive procedures, diagnose skin cancer with a photograph, predict adverse clinical events, and recommend treatments based on current literature. Getting these innovations to market requires access to large, complex data sets to train the AI models.
Artificial intelligence (AI) is rewiring the way we think about healthcare. And rewiring the way doctors predict, diagnose and treat disease, how exams are carried out and how health systems are run. Is AI a game-changer? Absolutely, and the game is changing a lot faster than many think.
A team from the Wellcome Sanger Institute in the United Kingdom, the University of Otago in New Zealand and the Helmholtz Institute for RNA-based Infection Research in Germany has developed a machine learning tool capable of detecting strains of salmonella before they cause bloodstream infections. Findings were published May 8 in PLOS Genetics.
May 03, 2018 | Mobile & Telehealth
TeleHealth Services has announced the launch of iCare Navigator, an interactive patient engagement system that uses virtual health coaches trained by artificial intelligence (AI) to address the shortage of nurses.
Stanford researchers, who have previously witnessed artificial intelligence (AI) performing on par with board-certified dermatologists, are turning to computer vision to ensure patient safety and improve physician hygiene.
Apr 20, 2018 | Interoperability
TriHealth, a Cincinnati-based health system, has announced a $10 million-dollar investment to implement the IBM Watson Health’s Enterprise Imaging Portfolio.
Apr 12, 2018 | Clinical Practice
A machine learning, real-time hand hygiene notification system improved participant adherence to 100 percent, according to a study published April 9 in the Journal of Hospital Infection.