Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Neural Networks for Pulmonary Disease Diagnosis using Auditory and
  Demographic Information   Pulmonary diseases impact millions of lives globally and annually. The recent
outbreak of the pandemic of the COVID-19, a novel pulmonary infection, has more
than ever brought the attention of the research community to the machine-aided
diagnosis of respiratory problems. This paper is thus an effort to exploit
machine learning for classification of respiratory problems and proposes a
framework that employs as much correlated information (auditory and demographic
information in this work) as a dataset provides to increase the sensitivity and
specificity of a diagnosing system. First, we use deep convolutional neural
networks (DCNNs) to process and classify a publicly released pulmonary auditory
dataset, and then we take advantage of the existing demographic information
within the dataset and show that the accuracy of the pulmonary classification
increases by 5% when trained on the auditory information in conjunction with
the demographic information. Since the demographic data can be extracted using
computer vision, we suggest using another parallel DCNN to estimate the
demographic information of the subject under test visioned by the processing
computer. Lastly, as a proposition to bring the healthcare system to users'
fingertips, we measure deployment characteristics of the auditory DCNN model
onto processing components of an NVIDIA TX2 development board.

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The categories of this paper are: q-bio
27
The categories of this paper are: comp-gas
12
The categories of this paper are: nucl-th
34
The categories of this paper are: chem-ph
6
The categories of this paper are: astro-ph
26
The categories of this paper are: bayes-an
23
The categories of this paper are: solv-int
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The categories of this paper are: nucl-ex
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The categories of this paper are: hep-ex
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The categories of this paper are: patt-sol
3
The categories of this paper are: physics
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The categories of this paper are: q-fin
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The categories of this paper are: eess
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The categories of this paper are: hep-lat
32
The categories of this paper are: atom-ph
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The categories of this paper are: plasm-ph