Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Unsupervised learning with GLRM feature selection reveals novel
  traumatic brain injury phenotypes   Baseline injury categorization is important to traumatic brain injury (TBI)
research and treatment. Current categorization is dominated by symptom-based
scores that insufficiently capture injury heterogeneity. In this work, we apply
unsupervised clustering to identify novel TBI phenotypes. Our approach uses a
generalized low-rank model (GLRM) model for feature selection in a procedure
analogous to wrapper methods. The resulting clusters reveal four novel TBI
phenotypes with distinct feature profiles and that correlate to 90-day
functional and cognitive status.

32
The categories of this paper are: atom-ph
0
The categories of this paper are: hep-ph
8
The categories of this paper are: hep-ex
28
The categories of this paper are: alg-geom
7
The categories of this paper are: hep-th
3
The categories of this paper are: physics
15
The categories of this paper are: nucl-ex
17
The categories of this paper are: q-fin
31
The categories of this paper are: ao-sci
24
The categories of this paper are: dg-ga
22
The categories of this paper are: chao-dyn
14
The categories of this paper are: math-ph
23
The categories of this paper are: solv-int
29
The categories of this paper are: funct-an
27
The categories of this paper are: comp-gas
34
The categories of this paper are: chem-ph