Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Challenges for machine learning in clinical translation of big data
  imaging studies   The combination of deep learning image analysis methods and large-scale
imaging datasets offers many opportunities to imaging neuroscience and
epidemiology. However, despite the success of deep learning when applied to
many neuroimaging tasks, there remain barriers to the clinical translation of
large-scale datasets and processing tools. Here, we explore the main challenges
and the approaches that have been explored to overcome them. We focus on issues
relating to data availability, interpretability, evaluation and logistical
challenges, and discuss the challenges we believe are still to be overcome to
enable the full success of big data deep learning approaches to be experienced
outside of the research field.

2
The categories of this paper are: math
14
The categories of this paper are: math-ph
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
12
The categories of this paper are: nucl-th
22
The categories of this paper are: chao-dyn
15
The categories of this paper are: nucl-ex
24
The categories of this paper are: dg-ga
7
The categories of this paper are: hep-th
35
The categories of this paper are: mtrl-th
26
The categories of this paper are: bayes-an
30
The categories of this paper are: q-alg
25
The categories of this paper are: patt-sol
8
The categories of this paper are: hep-ex
21
The categories of this paper are: adap-org
37
The categories of this paper are: supr-con