Carestream Health has released Smart Noise Cancellation (SNC), a groundbreaking artificial intelligence (AI)-based technology that greatly improves image quality — producing images that are significantly clearer than with standard processing.
Researchers used AI to identify which daily changing clinical parameters best predict intervention responses in critically ill Covid-19 patients. The investigators used machine learning to predict which patients might get worse and not respond positively to being turned onto their front in intensive care units (ICUs) - a technique known as proning that is commonly used in this setting to improve…
A new research project will embrace the combination of 5G telecommunications technology and AI to offer continuous remote monitoring to seriously ill heart failure patients, for example those with Left Ventricular Assist Devices (LVADs).
Is artificial intelligence (AI) technology ready to be utilized as a clinical tool by interventional oncologists? Not yet, but when it is, AI technology’s clinical impact may be as profound as advanced imaging is today, two leading experts agree.
Researchers from Tel Aviv University have created an artificial intelligence platform that can identify the specific proteins that allow bacteria to infect the intestines.
Robotics, AI, and machine learning can make spinal surgery more accurate, efficient, and safer, thereby reducing costs, patient recovery time, and radiation exposure.
A test which uses artificial intelligence (AI) to measure proteins present in some patients with advanced bowel cancer could hold the key to more targeted treatment, according to new research. A team at the University of Leeds collaborated with researchers at Roche Diagnostics to develop the technique, which will help doctors and patients to decide on the best treatment options.
Kobe University Hospital’s Dr. Makoto Nishimori and Project Assistant Professor Kunihiko Kiuchi et al. (of the Division of Cardiovascular Medicine, Department of Internal Medicine) have developed an AI that uses multiple kinds of test data to predict the location of surplus pathways in the heart called ‘accessory pathways’, which cause the heart to beat irregularly. In this study, the…
An artificial intelligence (AI)-driven system that automatically combs through brain MRIs for abnormalities could speed care to those who need it most, according to a new study. “There are an increasing number of MRIs that are performed, not only in the hospital but also for outpatients, so there is a real need to improve radiology workflow,” said study co-lead author Romane Gauriau, PhD,…
In just the last two years, artificial intelligence has become embedded in scores of medical devices that offer advice to ER doctors, cardiologists, oncologists, and countless other health care providers. But how much do either regulators or doctors really know about the accuracy of these tools? A new study led by researchers at Stanford, some of whom are themselves developing devices, suggests…
Researchers from the Canadian University Healh Network (UHN) have developed and validated a deep learning model to predict a patient's long-term outcome after receiving a liver transplant. First of its kind in the field of Transplantation, this model is the result of a collaboration between the Ajmera Transplant Centre and Peter Munk Cardiac Centre (PMCC). The study, published in Lancet Digital…
Over the past decade, hospitals and other healthcare providers have put massive amounts of time and energy into adopting electronic healthcare records, turning hastily scribbled doctors' notes into durable sources of information. But collecting these data is less than half the battle. It can take even more time and effort to turn these records into actual insights — ones that use the learnings…
The U.S. Food and Drug Administration authorized marketing of the GI Genius, the first device that uses artificial intelligence (AI) based on machine learning to assist clinicians in detecting lesions (such as polyps or suspected tumors) in the colon in real time during a colonoscopy. “Artificial intelligence has the potential to transform health care to better assist health care providers and…
Royal Philips and Ibex Medical Analytics announced a strategic collaboration to jointly promote their digital pathology and AI solutions to hospitals, health networks and pathology labs worldwide. The combination of Philips digital pathology solution (Philips IntelliSite Pathology Solution) and Ibex’s Galen AI-powered cancer diagnostics platform, currently in clinical use in Europe and the…
What’s in a name? In the case of Asensus Surgical, Inc., previously known as TransEnterix, Inc., the recent rebranding doubles as a mission statement for the manufacturer of surgical robotics systems: The initial ‘A’ stands for artificial intelligence and augmented surgery, reflecting the company’s emphasis on new technologies designed to enhance the operator’s cognition (‘sensus’…
Medical technology company iCAD, Inc. announced that ProFound AI for 2D Mammography might notably reduce the risk of interval breast cancer, according to a new retrospective analysis. The aim of the study was to determine if adding AI to reading mammography as a supportive tool may help in decreasing the interval cancer rate in population-based organized mammography screening programs in Germany.
Experts from Sweden, Finland and Kenya are using digital microscopy combined with Artificial Intelligence (AI) to deliver a rapid and effective cervical screening service to rural locations in Kenya. The project sees AI and digital diagnostics bridge the gap between low-resource settings and the availability of centralised AI-enhanced expertise and pathology services, located in larger cities in…
Emerging technologies can screen for cervical cancer better than Pap smears and, if widely used, could save lives both in developing nations and parts of countries, like the United States, where access to health care may be limited. In Biophysics Reviews, by AIP Publishing, scientists at Massachusetts General Hospital write advances in nanotechnology and computer learning are among the…
International genomics research led by the University of Leicester has used artificial intelligence (AI) to study an aggressive form of cancer, which could improve patient outcomes. Mesothelioma is caused by breathing asbestos particles and most commonly occurs in the linings of the lungs or abdomen. Currently, only seven per cent of people survive five years after diagnosis, with a prognosis…
Healthy and cancer cells can look similar under a microscope. One way of differentiating them is by examining the level of acidity, or pH level, inside the cells. Tapping on this distinguishing characteristic, a research team from the National University of Singapore (NUS) has developed a technique that uses artificial intelligence (AI) to determine whether a single cell is healthy or cancerous…
From swallowing pills to injecting insulin, patients frequently administer their own medication. But they don’t always get it right. Improper adherence to doctors’ orders is commonplace, accounting for thousands of deaths and billions of dollars in medical costs annually. Researchers at the Massachusetts Institute of Technology (MIT) have developed a system to reduce those numbers for some…
Moderna and IBM announced their intentions to explore technologies, including artificial intelligence, blockchain and hybrid cloud, that could help support smarter Covid-19 vaccine management. Central to the effort will be a pilot of open, standardized, technology-enabled vaccine distribution approaches aimed to improve supply chain visibility and foster near real-time tracking of vaccine…
Parkinson’s disease (PD) usually causes facial abnormalities that affect a person’s self-esteem and relationships. However, these abnormalities are difficult to analyze quantitatively with current methods. To address this issue, scientists from Okayama University, Japan, explored whether commercial AI-based facial analysis software could be useful in this context. Their results show that…
Systematic review finds that machine learning models for detecting and diagnosing Covid-19 from medical images have major flaws and biases, making them unsuitable for use in patients. However, researchers have suggested ways to remedy the problem. Researchers have found that out of the more than 300 Covid-19 machine learning models described in scientific papers in 2020, none of them is suitable…
The results of a large-scale study indicate that the introduction of an AI-powered solution by healthcare software company Radlogics into radiology workflow to analyze Chest-CT scans during the Covid-19 pandemic reduced report turnaround time by an average of 30 percent, which is equivalent to 7 minutes per case.