Cardiologists in the UK are trialling an artificial intelligence (AI) system that will help better diagnose heart disease. Devised by researchers from the University of Oxford, it can predict heart disease and cardiac events from ultrasound stress test images with initial results showing that the AI system is far more accurate than conventional techniques. Paul Leeson, Professor of Cardiovascular…
The new 1.5 Tesla MRI from Siemens Healthineers, Magnetom Sola, is packed with helpful algorithms and other functions. AI-supported systems monitor patients and scan parameters and ensure consistent image quality. Whilst visitors at this year’s ECR-Expo admired the new device, Prof. Ulrike Attenberger has already tested it in practice.
Growth! New hardware, new software, richer imaging, enhanced communication and image transfer plus artificial intelligence (AI) are all pushing the pace that medical organisations, radiologists and device manufacturers must run to keep up. We spoke with Dr Erik Ranschaert, President of EuSOMII, about today’s changing face of radiology.
Recent developments in artificial intelligence (AI) created a veritable hype. However, that initial awe was increasingly mixed with apprehension about the potential effects of AI on healthcare. In radiology, bleak dystopias are conjured up with AI replacing the human radiologist. A scenario that Dr Felix Nensa considers premature, to say the least.
The selection of a first-line chemotherapy drug to treat many types of cancer is often a clear-cut decision governed by standard-of-care protocols, but what drug should be used next if the first one fails? That’s where Georgia Institute of Technology researchers believe their new open source decision support tool could come in. Using machine learning to analyze RNA expression tied to…
Royal Philips has been leading two healthcare innovation projects that will receive government investment as part of major cross-sector collaborations with the NHS, academia and industry partners from the UK Government’s Industrial Strategy Challenge Fund, delivered through United Kingdom Research and Innovation (UKRI). A joint multi-million pound investment by government and industry partners,…
A deep neural network algorithm called BOTA uses bacterial genomes to identify unrecognized bacterial antigens.
Standardised and well-structured data, as well as the definition of clear objectives, are indispensable prerequisites for artificial intelligence implementation into clinical processes. ‘Ask not what artificial intelligence can do for you but what you can do for artificial intelligence!’ This variation on John F Kennedy’s famous quote comes from Dr Ben Glocker, Senior Lecturer in Medical…
Often referred to as the ‘Achilles’ heel’ of histopathology, the sample entry has posed considerable challenges in pre-analytics for several decades. We visited the Munich-based lab automation start-up Inveox GmbH. Time-intense, highly manual processes in labs are expensive, error-prone and the most common reason for irregularities in cancer diagnoses. In Germany alone, every year hundreds…
'Image Computing, including image analysis, artificial intelligence, artificial neural networks und deep learning, is starting a revolution,’ says Dr Paul Suetens, professor of Medical Imaging and Image Processing at University Hospital Leuven. Artificial Intelligence (AI) is not new – research in this field was carried out as far back as the 1950s – but, whilst in the early days AI learnt…
Synergy is key to ensuring Artificial Intelligence (AI) can play a critical role in helping radiologists raise their game. Integrating AI with innovative platforms to optimise workflow and make diagnosis more efficient, whilst also creating more accurate reports, offers enormous potential benefits to patients, clinicians and hospitals, according to industry specialist Tomer Zonens, Worldwide…
Imagine a first responder answering the call to a natural disaster, a house fire, or an active shooter incident where there may be multiple injuries and unknown casualties. The information the responder needs to fulfill the mission is immeasurable. When you also consider the volume of data they receive from other responders, dispatch, command centers, victims, and onlookers while receiving and…
A pathology test that applies artificial intelligence (AI) to characterize tissue samples can accurately predict clinically significant prostate cancer disease progression following surgery, according to a study conducted at the Icahn School of Medicine at Mount Sinai.
Machine learning is increasingly helping radiologists to acquire faster and better quality images, and measure heart function. This is just the tip of the iceberg; artificial intelligence has far more to bring to the heart, explained Daniel Rueckert, Head of the Department of Computing at Imperial College London, during CMR 2018. Machine learning (ML) is becoming a valuable assistant for…
Neuroscientist Lynda Chin MD, Founder and CEO of Real-world Education Detection and Intervention, has little doubt: ‘Artificial intelligence to the rescue,’ she proclaimed in her keynote address at the Artificial Intelligence and Machine Learning Summit, held in Las Vegas this spring. ‘We need a system and analytics to interpret data!’ she urged, despite being well aware that building a…
Using a new approach called 'reinforced learning', researchers have taught an artificial intelligence (AI) to responsibly choose the right amount of chemo- and radiotherapy for glioblastoma patients. The technique, which is insprired by behavioural psychology, has given the AI the ability to master the tightrope walk between effective tumor shrinkage and the medications' severe side effects.
A multidisciplinary team of researchers from the National University of Singapore (NUS) has developed an artificial intelligence (AI) technology platform that could potentially change the way drug combinations are being designed, hence enabling doctors to determine the most effective drug combination for a patient quickly. Applying the platform towards drug resistant multiple myeloma, a type of…
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…
