Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multi-task multiple kernel machines for personalized pain recognition
  from functional near-infrared spectroscopy brain signals   Currently there is no validated objective measure of pain. Recent
neuroimaging studies have explored the feasibility of using functional
near-infrared spectroscopy (fNIRS) to measure alterations in brain function in
evoked and ongoing pain. In this study, we applied multi-task machine learning
methods to derive a practical algorithm for pain detection derived from fNIRS
signals in healthy volunteers exposed to a painful stimulus. Especially, we
employed multi-task multiple kernel learning to account for the inter-subject
variability in pain response. Our results support the use of fNIRS and machine
learning techniques in developing objective pain detection, and also highlight
the importance of adopting personalized analysis in the process.

18
The categories of this paper are: econ
9
The categories of this paper are: nlin
20
The categories of this paper are: acc-phys
8
The categories of this paper are: hep-ex
36
The categories of this paper are: cmp-lg
27
The categories of this paper are: comp-gas
21
The categories of this paper are: adap-org
19
The categories of this paper are: eess
3
The categories of this paper are: physics
30
The categories of this paper are: q-alg
11
The categories of this paper are: hep-lat
22
The categories of this paper are: chao-dyn
32
The categories of this paper are: atom-ph
23
The categories of this paper are: solv-int
25
The categories of this paper are: patt-sol
4
The categories of this paper are: cond-mat