Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Inference of a Multi-Domain Machine Learning Model to Predict Mortality
  in Hospital Stays for Patients with Cancer upon Febrile Neutropenia Onset   Febrile neutropenia (FN) has been associated with high mortality, especially
among adults with cancer. Understanding the patient and provider level
heterogeneity in FN hospital admissions has potential to inform personalized
interventions focused on increasing survival of individuals with FN. We
leverage machine learning techniques to disentangling the complex interactions
among multi domain risk factors in a population with FN. Data from the
Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample and
Nationwide Inpatient Sample (NIS) were used to build machine learning based
models of mortality for adult cancer patients who were diagnosed with FN during
a hospital admission. In particular, the importance of risk factors from
different domains (including demographic, clinical, and hospital associated
information) was studied. A set of more interpretable (decision tree, logistic
regression) as well as more black box (random forest, gradient boosting, neural
networks) models were analyzed and compared via multiple cross validation. Our
results demonstrate that a linear prediction score of FN mortality among adults
with cancer, based on admission information is effective in classifying high
risk patients; clinical diagnoses is the domain with the highest predictive
power. A number of the risk variables (e.g. sepsis, kidney failure, etc.)
identified in this study are clinically actionable and may inform future
studies looking at the patients prior medical history are warranted.

15
The categories of this paper are: nucl-ex
19
The categories of this paper are: eess
37
The categories of this paper are: supr-con
8
The categories of this paper are: hep-ex
20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
0
The categories of this paper are: hep-ph
34
The categories of this paper are: chem-ph
28
The categories of this paper are: alg-geom
24
The categories of this paper are: dg-ga
26
The categories of this paper are: bayes-an
14
The categories of this paper are: math-ph
35
The categories of this paper are: mtrl-th
21
The categories of this paper are: adap-org
30
The categories of this paper are: q-alg
7
The categories of this paper are: hep-th