A team of researchers are developing the use of an artificial intelligence (AI) algorithm with the aim of diagnosing deep vein thrombosis (DVT) more quickly and as effectively as traditional radiologist-interpreted diagnostic scans, potentially cutting down long patient waiting lists and avoiding patients unnecessarily receiving drugs to treat DVT when they don't have it. DVT is a type of blood clot most commonly formed in the leg, causing swelling, pain and discomfort--if left untreated, it can lead to fatal blood clots in the lungs. Researchers at Oxford University, Imperial College and the University of Sheffield collaborated with the tech company ThinkSono (which is led by Fouad Al-Noor and Sven Mischkewitz), to train a machine learning AI algorithm (AutoDVT) to distinguish patients who had DVT from those without DVT. The AI algorithm accurately diagnosed DVT when compared to the gold standard ultrasound scan, and the team worked out that using the algorithm could potentially save health services $150 per examination. "Traditionally, DVT diagnoses need a specialist ultrasound scan performed by a trained radiographer, and we have found that the preliminary data using the AI algorithm coupled to a hand-held ultrasound machine shows promising results," said study lead Dr. Nicola Curry, a researcher at Oxford University's Radcliffe Department of Medicine and clinician at Oxford University Hospitals NHS Foundation Trust.
The Transform Technology Summits start October 13th with Low-Code/No Code: Enabling Enterprise Agility. Arm unveiled some new tools for chipmakers and car makers to developed "software-defined" automobiles of the future. Software-defined automobiles are those that can be reprogrammed for different functions using software, even after the cars ship to owners. Cambridge, England-based Arm is working with major automobile suppliers and tech firms including AWS, Continental, Cariad, and more. The car features range from driver-assisted safety measures to self-driving cars. But the one thing they share in common is that they're loaded with electronics.
Artificial intelligence could spot the early signs of dementia from a simple brain scan long before major symptoms appear – and in some cases before any symptoms appear – say Cambridge researchers. Dementias are characterized by the build-up of different types of protein in the brain, which damages brain tissue and leads to cognitive decline. In the case of Alzheimer's disease, these proteins include beta-amyloid, which forms'plaques', clumping together between neurons and affecting their function, and tau, which accumulates inside neurons. Molecular and cellular changes to the brain usually begin many years before any symptoms occur. Diagnosing dementia can take many months or even years.
The Government has said that artificial intelligence (AI) in GP practices will help manage patients in the elective care backlog. It today announced that new technology and innovation will allow the NHS to treat 30% more elective care patients by 2023/24. It added that NHS'come forward with a delivery plan for tackling the backlog'. In March, NHS England suggested that GPs could be asked to review hospital waiting lists for elective care to help prioritise and manage patients from the following month. Details were limited, but NHS England later told GPs that they must'jointly manage' patients stuck in the backlog of care caused by the Covid pandemic with hospitals. Meanwhile, Pulse revealed in June that NHSX and NHS England were considering the viability of a wider roll out of an artificial intelligence triage model based on that used by Babylon.
Artificial intelligence (AI) could diagnose a suspected dementia patient the day they are assessed. The disease currently has no set test, with medics generally relying on cognitive assessments and brain scans. With it sometimes taking years to reach a diagnosis, scientists from the University of Cambridge are developing an AI system that could spot signs of the disease after a single brain scan. The system is "trained" to compare a suspected patient's brain scan against thousands of confirmed cases, with the algorithm potentially identifying signs of the disease that a neurologist could not spot. Although the technology is still in a trial stage, it could diagnose dementia years before symptoms emerge.
So far for Alex Kendall, everything is on track. Since founding his driverless-car tech start-up Wayve in 2017, he has raised more than $44 million (£32 million) from investors, assembled a team of 100 and opened a flashy HQ in King's Cross, the heart of London's artificial intelligence (AI) industry. The Cambridge University graduate now has his sights set on rolling out his product on the roads, but much like one of his autonomous Jaguar I-Pace cars, it is something he cannot control. "We've built a team and put together a technology ... [but] there's no legislation currently in place to support autonomous driving in the UK," said Kendall, 29.
NIHR awards £12 million to artificial intelligence research to help understand multiple long-term conditions. Professor Bruce Guthrie will lead one of three new Research Collaborations. The NIHR has awarded almost £12 million to new research that will use advanced data science and artificial intelligence (AI) methods to identify and understand clusters of multiple long-term conditions and develop ways to prevent and treat them. An estimated 14 million people in England are living with two or more long-term conditions, with two-thrids of adults aged over 65 expected to be living with multiple long-term conditions by 2035. People who develop multiple long-term conditions often do not have a random assortment of diseases but rather a largely predictable cluster of conditions.
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Artificial intelligence (AI) is transforming the way we live, work, travel, and do business. The expertise of British AI companies, some of the world's most innovative, contributes significantly to this increase in global economic growth and productivity. Recently, Tech Nation, the leading growth platform for UK tech companies, released data on the growth of the AI tech ecosystem in the UK. According to this new data, the UK is now home to over 1,300 AI companies, up from 180 companies in 2011, representing a 600% increase. AI companies are scaling across all regions of the UK, with 50% of the top scaling AI companies being outside of London with Cambridge and Edinburgh being major hubs. Furthermore, Venture Capital investment into UK AI companies also rocketed from $120 million in 2010 to $3.4 billion in 2020.