How prediction machines have become infrastructure for the legitimacy of event outcomes, no matter how outlandish.
MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...
Models using established cardiovascular disease risk factors had satisfactory predictive performance for 5-year CVD risk in ...
Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global ...
Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...
Researchers developed a machine learning model that could identify children in the ED who were at risk for developing sepsis ...
Disinfecting drinking water prevents the spread of deadly waterborne diseases by killing infectious agents such as bacteria, ...
Predictive orchestration is replacing siloed planning models. AI-powered control towers now integrate procurement, ...
An interatomic potential is a set of mathematical rules that describes the complex dance of forces between atoms — how atomic ...
In the past decade, cloud-scale analytics tools have transformed the digital fight against deforestation. Instead of manual ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
When pitching the use of a model, data scientists rarely report on its potential value. They then experience an unnerving ...
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