It’s long past asking “if” artificial intelligence (AI) and related technologies will revolutionize healthcare. According to a recent survey, 80 percent of executives expect AI will be integrated into the patient experience within two years. At the same time, 81 percent of respondents agree their organizations are not ready for the societal and liability issues that will result from this change.
Researchers from the New York University Rory Meyers College of Nursing have found machine learning using real-time symptom reports to be accurate in identifying lymphedema early in breast cancer patients. Findings were published in the May 2018 issue of mHealth.
Artificial intelligence (AI) in medical devices may lead to breakthroughs for self-management in patients with diabetes, according to a study published May 31 in the Journal of Medical Internet Research.
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 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.
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.
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.