Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Preterm Birth Prediction: Deriving Stable and Interpretable Rules from
  High Dimensional Data   Preterm births occur at an alarming rate of 10-15%. Preemies have a higher
risk of infant mortality, developmental retardation and long-term disabilities.
Predicting preterm birth is difficult, even for the most experienced
clinicians. The most well-designed clinical study thus far reaches a modest
sensitivity of 18.2-24.2% at specificity of 28.6-33.3%. We take a different
approach by exploiting databases of normal hospital operations. We aims are
twofold: (i) to derive an easy-to-use, interpretable prediction rule with
quantified uncertainties, and (ii) to construct accurate classifiers for
preterm birth prediction. Our approach is to automatically generate and select
from hundreds (if not thousands) of possible predictors using stability-aware
techniques. Derived from a large database of 15,814 women, our simplified
prediction rule with only 10 items has sensitivity of 62.3% at specificity of
81.5%.

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The categories of this paper are: hep-lat
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The categories of this paper are: mtrl-th
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The categories of this paper are: atom-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: solv-int
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The categories of this paper are: math-ph
0
The categories of this paper are: hep-ph
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The categories of this paper are: physics
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The categories of this paper are: patt-sol
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The categories of this paper are: bayes-an
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The categories of this paper are: chem-ph
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The categories of this paper are: q-alg
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The categories of this paper are: plasm-ph
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The categories of this paper are: gr-qc
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The categories of this paper are: q-fin
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The categories of this paper are: acc-phys