NEWS
WARNER MUSIC GROUP ANNOUNCES PARTNERSHIP WITH MEDTECH COMPANY TO TRIAL ‘ MUSICAL MEDICINE ’
Warner Music Group , ( WMG ) the global music entertainment company , has announced a partnership with MediMusic , the British HealthTech start-up , to help trial ‘ music as medicine ’ to relieve pain , anxiety and stress . Through the partnership , MediMusic will conduct research testing in several closed Randomised Controlled Trials in both the US and UK where they will deliver playlists from WMG ’ s catalogue of music to various patients and sample groups and observe how they respond in real-time .
MediMusic ’ s proprietary algorithms extract the relevant features from the digital DNA of a piece of music , resulting in a fingerprint for healthcare use . Using Artificial Intelligence , Machine Learning and patient data , MediMusic then automatically creates personalised 20-minute playlists and plays the music through a streaming device called the MediBeat and a pair of headphones .
Playlist running order is designed to reduce heart rate and stress hormones , like cortisol , and promote relaxation through hormones like dopamine and oxytocin . A heart rate monitor worn on the wrist allows MediMusic to monitor the physiological effect of a piece of music , and if the listener ’ s heart rate does not respond as expected , MediMusic ’ s ‘ Digital Drip ’ uses AI and ML to swap out forthcoming playlist tracks to invoke slower relaxation . MediMusic also provides evidence based KPIs showing the service benefit and medication cost savings .
Michael Baines , VP , Digital Strategy and Business Development , WMG , said : “ Together with MediMusic , we ’ re thrilled to explore the transformative healing power of music in their ‘ music as medicine ’ trials – we are just beginning to scratch the surface of what ’ s possible .”
OXFORD-LED STUDY SHOWS HOW AI CAN DETECT ANTIBIOTIC RESISTANCE IN AS LITTLE AS 30 MINUTES
Researchers supported by the Oxford Martin Programme on Antimicrobial Resistance Testing at the University of Oxford have reported advances towards a novel and rapid antimicrobial susceptibility test that can return results within as little as 30 minutes .
In their study published in Communications Biology , the team used a combination of fluorescence microscopy and Artificial Intelligence ( AI ) to detect antimicrobial resistance ( AMR ). This method relies on training deep-learning models to analyse bacterial cell images and detect structural changes that may occur in cells when they are treated with antibiotics . The method was shown to be effective across multiple antibiotics , achieving at least 80 % accuracy on a per-cell basis .
The researchers say their model could be used to identify whether cells in clinical samples are resistant to a range of a wide variety of antibiotics in the future .
The deep-learning models were able to detect antibiotic resistance reliably and at least 10 times faster than established state-of-the art clinical methods considered to be gold standard .
Co-author of the paper Achillefs Kapanidis , Professor of Biological Physics and Director of the Oxford Martin Programme on Antimicrobial Resistance Testing , said : “ Our AI-based approach detects such changes reliably and rapidly . Equally , if a cell is resistant , the changes we selected are absent , and this forms the basis for detecting antibiotic resistance .”
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