COOKIES: By using this website you agree that we can place Google Analytics Cookies on your device for performance monitoring. |
University of Cambridge > Talks.cam > MRC Biostatistics Unit Seminars > BSU Seminar: "Challenges in risk prediction using routinely collected health data"
BSU Seminar: "Challenges in risk prediction using routinely collected health data"Add to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Alison Quenault. This will be a free online seminar. To register, click here: https://us02web.zoom.us/meeting/register/tZEkdOupqDspHtK1D30gXlBykdbIvLV8DMdH Identifying who is at highest risk of severe consequences of COVID -19, such as hospitalisation or death, is an important component of any policy response. One of the best sources of information on who experiences these events is linked electronic health record data. Using these data to identify high-risk patients, however, raises a number of methodological challenges. This talk discusses the use of linked primary care data within the OpenSAFELY platform to predict risk of COVID -19 mortality and the challenges of doing so. This talk is part of the MRC Biostatistics Unit Seminars series. This talk is included in these lists:
Note that ex-directory lists are not shown. |
Other listsData mining Cambridge Tech Talks Sensors CDT seminarsOther talksOral Session 8 SUMMER BREAK Electrons in novel materials, water, and their interplay Non-integrable KdV-like models: solitons, breathers, compactons and rogue waves Insights from Physical Chemistry into the Aerosol Route for Respiratory Disease Transmission Grand Rounds: From back pain to paralysis; what should we do with those discs? |