Keyword: AI

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Neuro-research

Brain-computer interfaces: Getting a Grasp on how we think

A world where machines can be controlled by thought alone – such is the promise of so-called brain-computer interfaces (BCI). BCIs are both hardware and software communication systems that read brain and nerve signals, convert those into electrical signals and translate human thoughts into machine commands. Developers of BCIs rely on artificial intelligence, neural network models and big data…

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Future of radiology

'Radiologists who do not use AI will be replaced by those who do'

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, consultant at the Institute of Diagnostic and Interventional Radiology and…

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Cardio app

AI system screens early Phase AFib

Here at Medica, the Taiwanese start-up Maisense is demonstrating Freescan, its artificial intelligence (AI) based solution to screen for stroke through the early detection of atrial fibrillation (AFib). Speaking of the system’s aims, Maisense summed up this huge health problem. ‘Every four minutes, someone dies of stroke. Thirteen percent of these are classified as haemorrhagic stroke. When…

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Surgical interventions

Technology and team spirit to ensure future talent

The number of surgical interventions in Germany over the last ten years has increased by around 30%, but it would be wrong to talk of a heyday – mainly due to a lack of young talent, says Prof. Dr. Jörg Fuchs. The president of the German Society of Surgery (DGCH) and director of the Clinic and Polyclinic for Paediatric Surgery and Paediatric Urology at Tübingen University Hospital talks about…

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Cardiology

AI system improves heart disease diagnosis

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…

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Innovations

Aiding radiologists to stride forward

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, Vice-President of EuSOMII, about today’s changing face of radiology. Alongside exceptional advances affecting radiologists,…

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Innovation

AI helpers simplify clinical MRI scans

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. The Vice Chair at the Institute of Clinical Radiology and…

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Artificial intelligence

UK Government and Philips consortium co-invest in digital pathology

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,…

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Connected laboratory

Digitisation and automation: Game-changers in histopathology?

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…

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AI structure

Machine Learning: into the pumpkin patch

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…

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Pilot project

Could AI 'Audrey' be the future first response assistant?

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…

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Reinforced learning

AI masters tightrope walk of cancer treatment dosage

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.

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Personalised drug treatment

AI approach to help myeloma patients

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…

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Heard at the 14th ECDP in Helsinki

Digital pathology: Sometimes AI can outperform experts

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…

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AI & Deep Learning

How to escape from data silos

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…

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Man against machine

AI is better than dermatologists at diagnosing skin cancer

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…

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Machine Learning

Finding the right algorithms to tackle big data

Executive Director of European Hospital, 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, Tracy…

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The impact of AI

Radiology and radiologists: a painful divorce

Artificial intelligence 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, the…

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Innovation

Siemens Healthineers debuts new thermocycler and AI-powered interpretation software

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…

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Digital Ecosystem

Siemens Healthineers offers new way to manage care gaps with AI

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…

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A discipline transforming

Adding value with AI in medical imaging

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.

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An era of turbulence and innovation

The birth and rebirth of imaging

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.

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