Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Logic-Based Learning Approach to Explore Diabetes Patient Behaviors   Type I Diabetes (T1D) is a chronic disease in which the body's ability to
synthesize insulin is destroyed. It can be difficult for patients to manage
their T1D, as they must control a variety of behavioral factors that affect
glycemic control outcomes. In this paper, we explore T1D patient behaviors
using a Signal Temporal Logic (STL) based learning approach. STL formulas
learned from real patient data characterize behavior patterns that may result
in varying glycemic control. Such logical characterizations can provide
feedback to clinicians and their patients about behavioral changes that
patients may implement to improve T1D control. We present both individual- and
population-level behavior patterns learned from a clinical dataset of 21 T1D
patients.

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The categories of this paper are: dg-ga
18
The categories of this paper are: econ
34
The categories of this paper are: chem-ph
25
The categories of this paper are: patt-sol
37
The categories of this paper are: supr-con
9
The categories of this paper are: nlin
33
The categories of this paper are: plasm-ph
11
The categories of this paper are: hep-lat
6
The categories of this paper are: astro-ph
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The categories of this paper are: alg-geom
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The categories of this paper are: acc-phys
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The categories of this paper are: nucl-th
7
The categories of this paper are: hep-th
4
The categories of this paper are: cond-mat
36
The categories of this paper are: cmp-lg
21
The categories of this paper are: adap-org