Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An Approach for Clustering Subjects According to Similarities in Cell
  Distributions within Biopsies   In this paper, we introduce a novel and interpretable methodology to cluster
subjects suffering from cancer, based on features extracted from their
biopsies. Contrary to existing approaches, we propose here to capture complex
patterns in the repartitions of their cells using histograms, and compare
subjects on the basis of these repartitions. We describe here our complete
workflow, including creation of the database, cells segmentation and
phenotyping, computation of complex features, choice of a distance function
between features, clustering between subjects using that distance, and survival
analysis of obtained clusters. We illustrate our approach on a database of
hematoxylin and eosin (H&E)-stained tissues of subjects suffering from Stage I
lung adenocarcinoma, where our results match existing knowledge in prognosis
estimation with high confidence.

17
The categories of this paper are: q-fin
2
The categories of this paper are: math
3
The categories of this paper are: physics
37
The categories of this paper are: supr-con
12
The categories of this paper are: nucl-th
18
The categories of this paper are: econ
16
The categories of this paper are: stat
8
The categories of this paper are: hep-ex
26
The categories of this paper are: bayes-an
35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
0
The categories of this paper are: hep-ph
14
The categories of this paper are: math-ph
15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys
28
The categories of this paper are: alg-geom