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Working with brain imaging data, Xinyi has a lot of cool figures to show off in her technical presentation. She walks us through the image-on-scalar regression model and how it is used to infer a personalized “baseline” brain image along with the effects of different cognitive diagnoses.
Xinyi continues the conversation on precision medicine research at SAMSI. Xinyi describes the challenges of combining genomic data with imaging data for modelling Alzheimer’s with the goal to supplement subjective diagnosis criteria with the more objective biomarkers.
John is back to show the how machine learning can vastly speed up the selection of mathematical models. His presentation provides great visual intuition on how machine learning methods can help select mathematical models, even as measurement noise increases. It’s a huge improvement over selecting models by hand!
John discusses his work in the precision medicine program at the Statistical and Applied Mathematical Sciences Institute (SAMSI) to model wound healing. He describes the physiological mechanisms of wound healing and how to select a applications that are appropriate for mathematical modelling.
Rita Hendricusdottir (Department of Engineering Science, University of Oxford) show cases a new tool to help innovators quickly assess the regulatory buden of their medical devices. From answering the simple question of “Is my invention a medical device?” to the complex considerations for “which classification is my device?” the Oxford Global Guidance tool is designed to facilitate this initial evaluation.
Mike McArdle, co-founder and Chief Product Officer at Lucid Dream VR, is back to walk us through applications of VR that helps clinicians train for rare events and better understand the patient’s experience.
Mike McArdle, co-founder and Chief Product Officer at Lucid Dream VR, breaks down the key technological factors that have led to the rapid increase in VR and AR solutions for the life sciences. He then walks us through two products helping companies and hospitals to accelerate training and talent development on their staff.
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You can find the Virtual Undergraduate Career Fair here: https://ww2.amstat.org/virtualcareerservice/
A mini-epsidoe with (fellow data science podcaster) Stephanie Hicks. Stephanie highlights the keynote speakers at SDSS 2020 along with the conference themes.
Stephanie will be returning in a few weeks to discuss her own research at the nexus of data science, genomics, and public health.
It’s not everyday that medical researchers give the world access to 13+ years of dense, high-quality critical care data. Intensivist Paul Elbers describes the data set along with the clinical priorities in collecting the data. Paul covers a range of topics including protecting the patients’ interests and anonymity, a clinician’s priorities when selecting clinical performance metrics, and the stages of validating predictive algorithms up to the stage of an RTC. The work done to create AmsterdamUMCdb is an incredible feat and a huge boon to the medical science profession.
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