Machine Learning & Global Health Network
@MLGlobalHealth
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We are researchers in the U.K., Copenhagen and Singapore, founded in 2022. Working on: epi, health, phylo, Bayesian ML, computational stats, and more
Joined June 2022
Level up your forecasting game! 📈 Join the SPHERE-PPL team for the launch of our Forecasting Contest Series. Kick-off webinar details below: 🗓️ Monday, March 31st, 2025 at 3 PM GMT 🔗 [Registration Link] Details: https://t.co/DTIGBBPb73
#Skills #Learning #ForecastingContest
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Predict the future of Lyme disease in the UK. Join our forecasting contest and help us better understand incidence rates. Click here to learn more: https://t.co/DTIGBBPb73
#LymeDiseasePrediction #UKHealth #DataChallenge #GetInvolved
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New study published in @Nature Medicine estimates that in 2021, 2.9 million children (4.2%) in the United States had experienced the death of at least one parent or a grandparent caregiver responsible for most of the basic needs of the child 🧵1/3 https://t.co/H3blip3Fa6
imperial.ac.uk
ORPHANHOOD - There has been a significant increase in orphanhood in the last two decades in the U.S., according to a new study.
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We’re very excited to be teaching this course in Cape Town. Come and join us!
NEW short course: Modern Stats & ML for Population Health in Africa. Join us @AIMSacza in Cape Town for 1 week of Gaussian processes, compartmental models, phylogenetics, and hands-on Stan sessions with real data. Details: https://t.co/8nVB8AozVG
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Many members of #MLGH attended IDM 2024 in Bangkok. It was a great opportunity to share our work on health economics, vector borne diseases, social contacts and to connect with top minds around the world working in infectious disease modeling!
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Big thanks to @alex_andorra & @ChrisWymant for a great #StanCon 2024 panel! We covered epidemiology vs biology, infectious diseases vs NCDs, generative emulators, graph GPs, sequential data collection, and, of course, #ProbabilisticProgramming.
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After the break we're trying our R skills in a hands on tutorial on INLA and spatiotemporal models run by André Ribeiro Amaral
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Marc Baguelin is showcasing the toolkit for infectious disease modeller, including many useful R packages
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Final talk on today is by Yu Chen, who is presenting her project on sexual networks from partner block data in Uganda
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Next up, Xiaoyue Xi is presenting her work on leveraging node level information in network inference
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Seth Flaxman now giving an overview of inferential machine learning and applications in public health and policy
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Staying on the infectious diseases topic, Bienfait Igiraneza is talking about his PhD work on HIV resistance
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Next we have Christian Morgenstern discussing the spatiotemporal risks of COVID-19 in England
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Mengyan Zhang now is presenting her work on Adaptive Learning for Public Policy
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It's our second in-person MLGH day, today @imperialcollege! First up is Sydney Tucker on Hope groups https://t.co/tzezxwADT6
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