Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Screening Mammogram Classification with Prior Exams   Radiologists typically compare a patient's most recent breast cancer
screening exam to their previous ones in making informed diagnoses. To reflect
this practice, we propose new neural network models that compare pairs of
screening mammograms from the same patient. We train and evaluate our proposed
models on over 665,000 pairs of images (over 166,000 pairs of exams). Our best
model achieves an AUC of 0.866 in predicting malignancy in patients who
underwent breast cancer screening, reducing the error rate of the corresponding
baseline.

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The categories of this paper are: mtrl-th
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The categories of this paper are: comp-gas
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The categories of this paper are: dg-ga
29
The categories of this paper are: funct-an
15
The categories of this paper are: nucl-ex
18
The categories of this paper are: econ
3
The categories of this paper are: physics
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The categories of this paper are: atom-ph
30
The categories of this paper are: q-alg
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The categories of this paper are: bayes-an
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The categories of this paper are: hep-th
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The categories of this paper are: nlin
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The categories of this paper are: cond-mat
2
The categories of this paper are: math
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The categories of this paper are: math-ph
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The categories of this paper are: ao-sci