The digital revolution in healthcare in the United States is marching steadily forward, spurred by federal government regulations and financial incentives, by technological innovations, and by the necessities of increasing healthcare treatment efficiency, of lowering its cost and economic impact, and of elevating communications among providers, patients and payers to the norms of the 21st…
Machine learning is adding a new dimension to pathology and already outperforming experts during some tasks, according to several speakers at the 14th European Congress on Digital Pathology (ECDP) who revealed up-to-date developments. However, whilst AI is set to herald a new future for digital pathology, Johan Lundin, associated professor for biomedical informatics and research director at the…
Artificial Intelligence (AI) and machine learning are poised to transform healthcare, potentially freeing practitioners across many disciplines from routine tasks and saving lives through efficient early detection. Offering insight into the health of both individuals and populations, these ’deep learning‘ algorithms have the potential to process vast amounts of data and identify warning…
Researchers have shown for the first time that a form of artificial intelligence or machine learning known as a deep learning convolutional neural network (CNN) is better than experienced dermatologists at detecting skin cancer. In a study published in the leading cancer journal Annals of Oncology, researchers in Germany, the USA and France trained a CNN to identify skin cancer by showing it more…
Tracy Accardi, Hologic’s Vice President (Global R&D), spoke of the importance of innovation, tomosynthesis, artificial intelligence/deep learning and open dialogue with the radiology community. Hologic addresses a broad spectrum of gynaecological, perinatal, aesthetic, skeletal and breast women’s health issues. To enhance this approach, Accardi, explained the importance of working closely…
AI-based applications will replace radiologists in some areas, the physicist Bram van Ginneken predicts. ‘The profession of radiologist will change profoundly,’ predicts Gram van Ginneken, Professor of Medical Image Analysis at Radboud University Medical Centre. The cause is automatic image analysis by computers (first published in a paper in 1963) and deep learning.
At the 28th European Congress of Clinical Microbiology and Infectious Diseases (ECCMID 2018), Fast Track Diagnostics, a Siemens Healthineers company, launches a new molecular thermocycler, the Fast Track cycler, and the complementary new FastFinder software. The Fast Track cycler is a compact platform that enables laboratories of all sizes to implement molecular testing with simplicity and speed…
At the 2018 HIMSS Annual Conference & Exhibition, Siemens Healthineers showcases the Proactive Follow-up solution as part of its Siemens Healthineers Digital Ecosystem. The application prompts the appropriate physician to initiate a medically necessary response based on care gaps identified. For example, an incidental finding, an abnormality that appears in a radiology report intended for a…
In the next five to 10 years, artificial intelligence is likely to fundamentally transform diagnostic imaging. This will by no means replace radiologists, but rather help to meet the rising demand for imaging examinations, prevent diagnostic errors, and enable sustained productivity increases.
Some time in the distant future artificial intelligence (AI) systems may displace radiologists and many other medical specialists. However, in a far more realistic future AI tools will assist radiologists by performing very complex functions with medical imaging data that are impossible or unfeasible today, according to a presentation at the RSNA/AAPM Symposium during the Radiological Society of…
Artificial intelligence (AI) technology and its role and future impact on the radiology profession was the dominant theme at RSNA 2017, whether in scientific presentations or in the technical exhibitions. Keith J Dreyer DO PhD addressed this subject head-on in his presentation ‘Healthcare AI – Radiology’s Next Frontier.’ Dr Keith Dreyer, vice chairman of radiology informatics and chief…
The New Horizons Lecture at the RSNA annual meeting is a keynote address that looks to the future, and the inventor of a major innovation in magnetic resonance imaging (MRI) technology, Daniel K Sodickson MD PhD, did just that. His lecture entitled ‘A New Light: The Birth and Rebirth of Imaging’ looked back at how MRI has evolved and forward at what it will become.
Google AI has made a breakthrough: successfully predicting cardiovascular problems such as heart attacks and strokes simply from images of the retina, with no blood draws or other tests necessary. This is a big step forward scientifically, Google AI officials said, because it is not imitating an existing diagnostic but rather using machine learning to uncover a surprising new way to predict these…
Researchers used machine learning techniques, including natural language processing algorithms, to identify clinical concepts in radiologist reports for CT scans, according to a study conducted at the Icahn School of Medicine at Mount Sinai and published in the journal Radiology. The technology is an important first step in the development of artificial intelligence that could interpret scans and…
Machine learning is playing an increasing role in computer-aided diagnosis, and Big Data is beginning to penetrate oncological imaging. However, some time may pass before it truly impacts on clinical practice, according to leading UK-based German researcher Professor Julia Schnabel, who spoke during the last ESMRMB annual meeting. Machine learning techniques are starting to reach levels of human…
Communicating with patients can be tough. Reminder pamphlets often go straight into the rubbish and emails are deleted before they are read. But one doctor found that chatbots could be a key to patient outreach. Brett Swenson, MD, is no stranger to digital health. He runs a concierge practice in Arizona and started working with EMRs about 20 years ago when they were first introduced. He said he…
The tech world descended upon Las Vegas this week for the annual Consumer Electronics Show, and plenty of health IT’s biggest players were in attendance. While much of the discussion was on consumer-friendly health tools and novel digital interventions, there were still a handful of products and discussions between executives and entrepreneurs focused on healthcare’s largest roadblocks —…
3-D visualisation, augmented reality, automated tumour classification – today, the Republic of China produces cutting-edge medical technology and it’s a long time since ‘Made in Taiwan’ stood for inferior, copied products. Over recent years, this island state has successfully morphed into a productive and, above all, innovative manufacturer of medical technology available on the world…
Automation might be the solution for many of the challenges radiologists and clinicians face today. Toshiba Medical, a Canon Group, is currently pushing the boundaries of what automation can accomplish and presenting their project in progress at this year's RSNA. Overwhelming volume of clinical data every day, limited access to relevant clinical information, missed findings and lack of…
GE Healthcare and NVIDIA announced they will deepen their 10-year partnership to bring the most sophisticated artificial intelligence (AI) to GE Healthcare’s 500,000 imaging devices globally and accelerate the speed at which healthcare data can be processed. The scope of the partnership, detailed at the 103rd annual meeting of the Radiological Society of North America (RSNA), includes the…
While there has been a lot of hype — and even fear — about the role deep learning (DL) and artificial intelligence (AI) play in radiology, the reality is that they are both potentially useful technologies that will add value to the specialty in a number of ways. "Deep Learning is not going to replace us," said Paul Chang, MD, of the University of the Chicago School of Medicine,…
Scientists are using Artificial Intelligence (AI) to support more effective breast cancer detection. The researchers at Massachusetts Institute of Technology (MIT) Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts General Hospital (MGH), and Harvard Medical School, are using the machine learning system to predict whether breast lesions identified from a biopsy will…
Early adoption of image analytical tools and artificial intelligence (AI) are crucial if health systems across Europe are to see the full potential of digital pathology, according to leading expert Professor Johan Lundin, Research Director at the Institute for Molecular Medicine Finland (FIMM) at the University of Helsinki. Although European institutions increasingly embrace digital pathology, he…
Every day we hear news about Artificial Intelligence (AI) impacting more and more aspects of our lives. Stories about autonomous vehicles would probably top a current list of AI news. With all the excitement coming with these promising AI technologies, we are also starting to understand the limitations. In a recent Las Vegas traffic accident involving an autonomous bus and a truck, the cited…
Automation continues to conquer healthcare, including diagnostic imaging. Christian Kollmann, Assistant Professor at the Centre for Medical Physics and Biomedical Technology, Medical University Vienna, Austria, highlights innovative software, fast hardware and artificial intelligence in ultrasound – today and in the future. Automated analyses are already supporting the diagnostic work-up. In…