Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Coupling weak and strong supervision for classification of prostate
  cancer histopathology images   Automated grading of prostate cancer histopathology images is a challenging
task, with one key challenge being the scarcity of annotations down to the
level of regions of interest (strong labels), as typically the prostate cancer
Gleason score is known only for entire tissue slides (weak labels). In this
study, we focus on automated Gleason score assignment of prostate cancer
whole-slide images on the basis of a large weakly-labeled dataset and a smaller
strongly-labeled one. We efficiently leverage information from both label
sources by jointly training a classifier on the two datasets and by introducing
a gradient update scheme that assigns different relative importances to each
training example, as a means of self-controlling the weak supervision signal.
Our approach achieves superior performance when compared with standard Gleason
scoring methods.

36
The categories of this paper are: cmp-lg
35
The categories of this paper are: mtrl-th
18
The categories of this paper are: econ
27
The categories of this paper are: comp-gas
15
The categories of this paper are: nucl-ex
19
The categories of this paper are: eess
11
The categories of this paper are: hep-lat
21
The categories of this paper are: adap-org
29
The categories of this paper are: funct-an
25
The categories of this paper are: patt-sol
10
The categories of this paper are: q-bio
0
The categories of this paper are: hep-ph
8
The categories of this paper are: hep-ex
31
The categories of this paper are: ao-sci
17
The categories of this paper are: q-fin
37
The categories of this paper are: supr-con