A.I. and virtual reality can determine neurosurgeon expertise with 90 per cent accuracy

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Machine learning-guided virtual reality simulators can help neurosurgeons develop the skills they need before they step in the operating room, according to a recent study. Research from the Neurosurgical Simulation and Artificial Intelligence Learning Centre at the Montreal Neurological Institute and Hospital (The Neuro) and McGill University shows that machine learning algorithms can accurately assess the capabilities of neurosurgeons during virtual surgery, demonstrating that virtual reality simulators using artificial intelligence can be powerful tools in surgeon training. Fifty participants were recruited from four stages of neurosurgical training; neurosurgeons, fellows and senior residents, junior residents, and medical students. They performed 250 complex tumour resections using NeuroVR, a virtual reality surgical simulator developed by the National Research Council of Canada and distributed by CAE, which recorded all instrument movements in 20 millisecond intervals. Using this raw data, a machine learning algorithm developed performance measures such as instrument position and force applied, as well as outcomes such as amount of tumour removed and blood loss, which could predict the level of expertise of each participant with 90 per-cent accuracy.


Click click snap: One look at patient's face, and AI can identify rare genetic diseases

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WASHINGTON D.C. [USA]: According to a recent study, a new artificial intelligence technology can accurately identify rare genetic disorders using a photograph of a patient's face. Named DeepGestalt, the AI technology outperformed clinicians in identifying a range of syndromes in three trials and could add value in personalised care, CNN reported. The study was published in the journal Nature Medicine. According to the study, eight per cent of the population has disease with key genetic components and many may have recognisable facial features. The study further adds that the technology could identify, for example, Angelman syndrome, a disorder affecting the nervous system with characteristic features such as a wide mouth with widely spaced teeth etc. Speaking about it, Yaron Gurovich, the chief technology officer at FDNA and lead researcher of the study said, "It demonstrates how one can successfully apply state of the art algorithms, such as deep learning, to a challenging field where the available data is small, unbalanced in terms of available patients per condition, and where the need to support a large amount of conditions is great."


Almost HALF of all autistic children can be cured of their phobias using virtual reality

Daily Mail - Science & tech

Virtual reality can cure autistic children of their phobias in 45 per cent of cases, and scientists claim the effects are permanent. A so-called Blue Room allows specialists to create a safe environment for patients to gently immerse themselves into stressful situations and work their way through various scenarios to confront and conquer their fears alongside a therapist. The treatment enabled 11-year-old schoolboy, Harry Mainwaring, to adopt and befriend a much-loved terrier. A separate study has also shown for the first time that the treatment works for some autistic adults. The team, from Newcastle University, created virtual environments which do not require goggles to explore.


How Facebook's brain-machine interface measures up

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Somewhat unceremoniously, Facebook this week provided an update on its brain-computer interface project, preliminary plans for which it unveiled at its F8 developer conference in 2017. In a paper published in the journal Nature Communications, a team of scientists at the University of California, San Francisco backed by Facebook Reality Labs -- Facebook's Pittsburgh-based division devoted to augmented reality and virtual reality R&D -- described a prototypical system capable of reading and decoding study subjects' brain activity while they speak. It's impressive no matter how you slice it: The researchers managed to make out full, spoken words and phrases in real time. Study participants (who were prepping for epilepsy surgery) had a patch of electrodes placed on the surface of their brains, which employed a technique called electrocorticography (ECoG) -- the direct recording of electrical potentials associated with activity from the cerebral cortex -- to derive rich insights. A set of machine learning algorithms equipped with phonological speech models learned to decode specific speech sounds from the data and to distinguish between questions and responses.


Machine learning-guided virtual reality simulators can be powerful tools in surgeon training

#artificialintelligence

Machine learning-guided virtual reality simulators can help neurosurgeons develop the skills they need before they step in the operating room, according to a new study. Research from the Neurosurgical Simulation and Artificial Intelligence Learning Centre at The Neuro (Montreal Neurological Institute and Hospital) and McGill University shows that machine learning algorithms can accurately assess the capabilities of neurosurgeons during virtual surgery, demonstrating that virtual reality simulators using artificial intelligence can be powerful tools in surgeon training. Fifty participants were recruited from four stages of neurosurgical training; neurosurgeons, fellows and senior residents, junior residents, and medical students. They performed 250 complex tumor resections using NeuroVR, a virtual reality surgical simulator developed by the National Research Council of Canada and distributed by CAE, which recorded all instrument movements in 20 millisecond intervals. Using this raw data, a machine learning algorithm developed performance measures such as instrument position and force applied, as well as outcomes such as amount of tumor removed and blood loss, which could predict the level of expertise of each participant with 90 per-cent accuracy.