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A machine learning model bests traditional methods for predicting cirrhosis mortality among hospitalized patients.
Based on data from its call center, a warranty company thought its market was predominantly female. However, when that ...
The probabilities of response are represented by a logistic regression model, in which variables in the survey are explanatory variables. The probabilities are estimated using a modified conditional ...
A machine learning model developed to predict 5-year survival in stage III colorectal cancer patients highlights key ...
Central bankers generally use the «Taylor rule» to guide their policy decisions, raising rates when inflation is above target ...
In Trump’s world, there is no Taylor rule or anything like it; there is just the demand for lower rates when he thinks it ...
Objective Longitudinal data from three UK birth cohorts (born in 1958, 1970 and 2001) were used to (1) document the historic ...
Early intervention in psoriatic arthritis (PsA) is disease-modifying, and delays in diagnosis, even by 6 months, can reduce ...
Background Cancer survivors have an increased risk of heart failure, but this is balanced by the risk of death from other ...
In this article, we propose a new variable importance measure, sparsity oriented importance learning (SOIL), for high-dimensional regression from a sparse linear modeling perspective by taking into ...