Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Unusual structures inherent in point pattern data predict colon cancer
  patient survival   Cancer patient diagnosis and prognosis is informed by assessment of
morphological properties observed in patient tissue. Pathologists normally
carry out this assessment, yet advances in computational image analysis provide
opportunities for quantitative assessment of tissue. A key aspect of that
quantitative assessment is the development of algorithms able to link image
data to patient survival. Here, we develop a point process methodology able to
describe patterns in cell distribution within cancerous tissue samples. In
particular, we consider the Palm intensities of two Neyman Scott point
processes, and a void process developed herein to reflect the spatial
patterning of the cells. An approximate-likelihood technique is taken in order
to fit point process models to patient data and the predictive performance of
each model is determined. We demonstrate that based solely on the spatial
arrangement of cells we are able to predict patient survival.

18
The categories of this paper are: econ
25
The categories of this paper are: patt-sol
9
The categories of this paper are: nlin
6
The categories of this paper are: astro-ph
8
The categories of this paper are: hep-ex
19
The categories of this paper are: eess
3
The categories of this paper are: physics
1
The categories of this paper are: cs
32
The categories of this paper are: atom-ph
20
The categories of this paper are: acc-phys
27
The categories of this paper are: comp-gas
14
The categories of this paper are: math-ph
4
The categories of this paper are: cond-mat
12
The categories of this paper are: nucl-th
31
The categories of this paper are: ao-sci
21
The categories of this paper are: adap-org