Ep 35: Christer Malmberg & rapid diagnostics. MALDI-TOF machine learning. Global burden of AMR. - podcast episode cover

Ep 35: Christer Malmberg & rapid diagnostics. MALDI-TOF machine learning. Global burden of AMR.

Feb 07, 20221 hr 3 min
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Episode description

Happy 2022 to you all! We are glad start a new year with you with this episode. This time, we bring you an interview with our first UAC PhD graduate, Christer Malmberg, who defended his industry-PhD thesis last year, where he developed a new rapid method of testing antibiotic susceptibility. We talk about his experience throughout his studies, what this new method brings to the table, and what he wishes for the future. In the news section, we continue talking about diagnostics, looking into a recent study that explores machine learning and the readily available MALDI-TOF system to provide early information that can help guide treatment recommendations for infections. We also talk about the new seminal paper published last month in The Lancet, presenting the most up-to-date and comprehensive data on the global burden of AMR. We hope you enjoy! Check relevant links in the show notes at www.uac.uu.se/the-amr-studio/episode35/. Follow our updates on twitter on www.twitter.com/uac_uu with #theAMRstudio hashtag! Theme music by Henrik Niss: www.tinyurl.com/henriknissspotify.
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Ep 35: Christer Malmberg & rapid diagnostics. MALDI-TOF machine learning. Global burden of AMR. | The AMR Studio podcast - Listen or read transcript on Metacast