Search Tag: machine learning
2019 27 Feb
The increasing number of emergency department (ED) visits often correlates with ED crowding and delays in care. This problem highlights the need for ED triage systems that accurately differentiate and prioritise critically ill from stable patients, enabling efficient allocation of finite ED resources. Currently, the Emergent Severity...Read more
2019 22 Feb
Radiologists, more than any other medical specialty, feel the professional and emotional ‘whiplash’ that began five or so years ago. Vanishing jobs (transforming radiologists into production units) for cost over quality for our patients, to the current shortage and need for more radiologists. AI introduced the threat that automation would take what...Read more
2019 22 Feb
In many ways Artificial Intelligence (AI) may seem like a new concept in healthcare, mainly due in part to the recent traction the topic has made in the news in the last few years. It has even been falsely sensationalized, to further elevate buzz, as a tool that will one day replace clinicians altogether. The truth, though, is that companies like Hologic,...Read more
2019 22 Feb
Artificial intelligence will alter healthcare as we know it, augmenting some jobs and outright replacing others. Though we can’t be sure when this will happen, what’s most important for now is understanding what AI is and what it isn’t. At medical conferences and in hospital cafeterias, few topics come up more frequently, or cause more confusion...Read more
2019 22 Feb
Artificial Intelligence Exhibition makes Grand Debut at this year’s ECR Making its grand debut at this year’s ECR, the Artificial Intelligence Exhibition (AIX) will bring AI to the heart of Europe’s biggest radiology congress and technical exhibition. Canon Medical is proud to have reached the sponsorship agreement of the AIX Theater. As...Read more
2019 15 Feb
Emergency medical dispatchers fail to identify approximately 25% of cases of out of hospital cardiac arrest, thus lose the opportunity to provide the caller instructions in cardiopulmonary resuscitation. This study examined whether a machine learning framework could recognize out-of-hospital cardiac arrest from audio files of calls to the emergency...Read more
2019 30 Jan
Enrolling seriously ill patients in intensive care units for clinical trials is often a big challenge for investigators. This is one reason why there is a dearth of evidence-based guidelines in critical medicine. For instance, ICU doctors often face a dilemma when it comes to ordering lab tests for specific patients. While ICU doctors are...Read more
2019 30 Jan
Needless to say, radiology plays a critical role in healthcare delivery. It is rare for a patient to pass through a hospital without requiring the opinion of a radiologist somewhere along their journey – be it in triaging patients in the ER , assessing the need for treatment, or evaluating the effectiveness of treatment. Equally important is...Read more
2019 29 Jan
Data forms an important part in clinician decision-making. This is one reason electronic health records serve as a useful and easy-to-access source of patient data and other information needed by care teams. How to make the most of valuable patient data in EHRs and put it to work for better personalised care will require more advanced technologies,...Read more
2019 21 Jan
Affidea launches new digital tools in its network to improve patient experience and boost operations workflow. Affidea, the leading pan-European provider of advanced diagnostic imaging, outpatient and cancer care services, has announced the launch of two new applications to drive forward the digitisation of its operations and increase productivity...Read more
2018 11 Dec
Radiology is being transformed by the exponential growth of machine learning and continuously emerging technologies like deep learning, part of the artificial intelligence (AI) revolution in the imaging field. Medical imaging and operations applications are transformed as new methods and algorithms are introduced into radiology’s daily practice. ...Read more
2018 07 Dec
Healthcare is seeing increased use of machine learning tools, which allows medical professionals to do their jobs more efficiently. A prime example is how machine learning has helped improve accuracy of a health system's readmission risk prediction model, resulting in a significant reduction in case managers' work hours. Bon Secours Charity Hospital's...Read more
2018 06 Dec
Artificial intelligence and machine learning are expected to revolutionise healthcare in the years to come. Cardiology is no exception. It is expected that AI and machine learning will provide cardiologists with a set of tools that will augment and extend their effectiveness. Some of the primary reasons why cardiologists need to embrace AI...Read more
2018 04 Dec
Radiology and medical imaging is continuously experiencing rapid enhancements including quality of patient care as a result of uncovering new aspects of the vast potential of artificial intelligence implementation in clinical practice. As more hospital medical imaging equipment connects to the internet, cyberattacks and malicious software vulnerabilities...Read more
2018 04 Dec
Cardiac arrest, a leading cause of admission to the intensive care unit (ICU), is associated with high mortality. Current illness severity scores perform poorly in predicting survival for this patient group. New research from Australia shows machine learning (ML) techniques can significantly increase the accuracy of estimating survival for ICU patients...Read more
2018 02 Dec
The tight roped tug of war concerning artificial intelligence and exponential technologies like deep learning and machine learning has been pulling at radiology for years. There are those fearing the dark side- new technologies as the ‘big bad’ machines that will rise up and exterminate the radiologist, the shining happy radiologists that see unicorns...Read more
2018 22 Nov
Amazon Web Services (AWS) has announced that Amazon Translate, Amazon Comprehend and Amazon Transcribe are now HIPAA eligible services. Through using machine learning, AWS provider and patient clientele can leverage data insights to deliver better healthcare outcomes. AWS HIPAA eligible services enable use of the secure AWS environment...Read more
2018 20 Nov
Machine learning can be used to analyse electronic health records and predict the risk of emergency hospital admissions, according to a new study from The George Institute for Global Health at the University of Oxford has found. You might also like: Hospital readmissions and machine learning The study is published in PLOS Medicine [open...Read more
2018 07 Nov
The potential impact of artificial intelligence in radiology is impressive; vendors and major academic centres are developing a wide array of artificial intelligence applications and neural networks to aid radiologists in clinical diagnosis and clinical decision support. Artificial intelligence (AI) is one of the trending topics in medicine...Read more
2018 14 Aug
UK researchers have demonstrated the application of a machine learning-based "red dot" model to classify chest radiographs as normal or abnormal, with 94.6% accuracy. Its application to real-world datasets may be warranted in optimising clinician workload in the face of expanding demand, according to the researchers. Their work is published in...Read more
2018 06 Jun
New research shows that a machine learning approach to predicting ICU readmission was significantly more accurate than previously published algorithms or prediction tools. Implementation of this approach could target patients who may benefit from additional time in the ICU or more frequent monitoring after transfer to the hospital ward, according...Read more
2018 23 May
Where is eHealth in Ireland heading and where could it lead us? Examining the state of eHealth, its challenges and opportunities at the European Association of Hospital Managers congress in Dublin. With digital innovations dramatically transforming every layer of the healthcare landscape, intensive discussions are required to manage...Read more
2018 23 May
Do AI and machine learning herald the end of radiology? I could answer in one word: Yes. But HealthManagement has given me 700 and I’m delighted to have the opportunity to expand my hypothesis. I might as well start with the “elephant in the room”. How many radiologists cringed when they read President Obama’s assertion that “radiologists...Read more