In the news | MSPoweruser
Microsoft Research has shown off a new technology which makes it easier to manage and spread your workspace intelligently over a variety of devices.
In the news | IEEE Spectrum
Imagine you're a farmer in the northern United States. It's early spring, and nighttime temperatures are just starting to rise above freezing. You need to fertilize your newly-planted crops, but you also know that at freezing temperatures, the fertilizer will…
How our research findings helped inform our UX directions to use the intelligent model in shaping how to smartly light up the automatic calculation capabilities to assist users to achieve their tasks efficiently without relying on a calculator.
In the news | IEEE Spectrum
Researchers at Microsoft have developed a framework called DeepMC that can very accurately predict local weather, and could be used by farmers, renewable energy producers, and others.
We have developed a globally applicable diagnostic COVID-19 model by augmenting the classical SIR epidemiological model with a neural network module. Our model does not rely upon previous epidemics like SARS/MERS and all parameters are optimized via machine learning algorithms…
Medications that target catecholamine-associated inflammation may prevent cytokine storm syndrome associated with COVID-19 and other diseases Preventing cytokin storm syndrom in Covid 19
Analyzing observational data from multiple sources can be useful for increasing statistical power to detect a treatment effect; however, practical constraints such as privacy considerations may restrict individual-level information sharing across data sets. This paper develops federated methods that only…
Alpha-1-adrenergic receptor antagonists (α1-blockers) can abrogate pro-inflammatory cytokines and may improve outcomes among patients with respiratory infections. Repurposing readily available drugs such as α1-blockers could augment the medical response to the COVID-19 pandemic. COVID-19 outcomes among hospitalized men with or…
OBJECTIVE: COVID-19 poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is…