Leiden University Medical Center (LUMC), Leiden University and Philips are jointly receiving over 2 million euros from NWO to set up an artificial intelligence (AI) lab. The aim of this lab is to accelerate and improve MRI scans with AI. This is great for patients, and it helps make MRI more accessible.
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An automated process that combines natural language processing and machine learning identified people who inject drugs (PWID) in electronic health records more quickly and accurately than current methods that rely on manual record reviews.
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Virtual Incision Corporation, a medical device company working on a miniaturized robotic-assisted surgery (RAS) platform, announced the U.S. Food and Drug Administration (FDA) has approved an Investigational Device Exemption (IDE) supplement to complete the final stage of its clinical study analyzing the MIRA Platform in bowel resection procedures. The approval was supported by a favorable interim clinical study report on the safety profile of MIRA.
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Engineering researchers have developed a hybrid machine-learning approach to muscle gesture recognition in prosthetic hands that combines an AI technique normally used for image recognition with another approach specialized for handwriting and speech recognition. The technique is achieving far superior performance than traditional machine learning efforts.
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Ganymed Robotics awarded a €2.5M grant from the European Commission
Ganymed Robotics, developer of software and robotics technologies for orthopedic surgeons, has secured a €2,5 M grant through the European Innovation Council (EIC) Accelerator program. EIC funding will help Ganymed bring its innovation to the millions of patients suffering from arthritis.
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University of Oxford and Oracle Cloud System helping researchers identify COVID-19 variants faster
The fast spread of the highly infectious Delta variant underscores the need for faster identification of COVID-19 mutations. Uniting governments and medical communities in this challenge, the University of Oxford and Oracle’s Global Pathogen Analysis System (GPAS) is now being used by organizations on nearly every continent.
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Researchers at the Beckman Institute for Advanced Science and Technology combined label-free microscopic imaging with artificial intelligence to quickly detect and classify SARS-CoV-2.
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Artificial intelligence models to analyze cancer images take shortcuts that introduce bias
Artificial intelligence tools and deep learning models are a powerful tool in cancer treatment. They can be used to analyze digital images of tumor biopsy samples, helping physicians quickly classify the type of cancer, predict prognosis and guide a course of treatment for the patient. However, unless these algorithms are properly calibrated, they can sometimes make inaccurate or biased predictions.
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Medical AI models rely on ‘shortcuts’ that could lead to misdiagnosis of COVID-19
Artificial intelligence promises to be a powerful tool for improving the speed and accuracy of medical decision-making to improve patient outcomes. From diagnosing disease, to personalizing treatment, to predicting complications from surgery, AI could become as integral to patient care in the future as imaging and laboratory tests are today.
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Communities benefit from sharing knowledge and experience among their members. Following a similar principle – called “swarm learning” – an international research team has trained artificial intelligence algorithms to detect blood cancer, lung diseases and COVID-19 in data stored in a decentralized fashion.
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