Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Towards automated patient data cleaning using deep learning: A
  feasibility study on the standardization of organ labeling   Data cleaning consumes about 80% of the time spent on data analysis for
clinical research projects. This is a much bigger problem in the era of big
data and machine learning in the field of medicine where large volumes of data
are being generated. We report an initial effort towards automated patient data
cleaning using deep learning: the standardization of organ labeling in
radiation therapy. Organs are often labeled inconsistently at different
institutions (sometimes even within the same institution) and at different time
periods, which poses a problem for clinical research, especially for
multi-institutional collaborative clinical research where the acquired patient
data is not being used effectively. We developed a convolutional neural network
(CNN) to automatically identify each organ in the CT image and then label it
with the standardized nomenclature presented at AAPM Task Group 263. We tested
this model on the CT images of 54 patients with prostate and 100 patients with
head and neck cancer who previously received radiation therapy. The model
achieved 100% accuracy in detecting organs and assigning standardized labels
for the patients tested. This work shows the feasibility of using deep learning
in patient data cleaning that enables standardized datasets to be generated for
effective intra- and interinstitutional collaborative clinical research.

8
The categories of this paper are: hep-ex
36
The categories of this paper are: cmp-lg
31
The categories of this paper are: ao-sci
19
The categories of this paper are: eess
24
The categories of this paper are: dg-ga
32
The categories of this paper are: atom-ph
28
The categories of this paper are: alg-geom
27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg
17
The categories of this paper are: q-fin
23
The categories of this paper are: solv-int
33
The categories of this paper are: plasm-ph
4
The categories of this paper are: cond-mat
16
The categories of this paper are: stat
7
The categories of this paper are: hep-th
0
The categories of this paper are: hep-ph