Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Machine Learning to Predict Developmental Neurotoxicity with
  High-throughput Data from 2D Bio-engineered Tissues   There is a growing need for fast and accurate methods for testing
developmental neurotoxicity across several chemical exposure sources. Current
approaches, such as in vivo animal studies, and assays of animal and human
primary cell cultures, suffer from challenges related to time, cost, and
applicability to human physiology. We previously demonstrated success employing
machine learning to predict developmental neurotoxicity using gene expression
data collected from human 3D tissue models exposed to various compounds. The 3D
model is biologically similar to developing neural structures, but its
complexity necessitates extensive expertise and effort to employ. By instead
focusing solely on constructing an assay of developmental neurotoxicity, we
propose that a simpler 2D tissue model may prove sufficient. We thus compare
the accuracy of predictive models trained on data from a 2D tissue model with
those trained on data from a 3D tissue model, and find the 2D model to be
substantially more accurate. Furthermore, we find the 2D model to be more
robust under stringent gene set selection, whereas the 3D model suffers
substantial accuracy degradation. While both approaches have advantages and
disadvantages, we propose that our described 2D approach could be a valuable
tool for decision makers when prioritizing neurotoxicity screening.

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The categories of this paper are: dg-ga
31
The categories of this paper are: ao-sci
2
The categories of this paper are: math
22
The categories of this paper are: chao-dyn
17
The categories of this paper are: q-fin
4
The categories of this paper are: cond-mat
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
32
The categories of this paper are: atom-ph
0
The categories of this paper are: hep-ph
30
The categories of this paper are: q-alg
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The categories of this paper are: alg-geom
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The categories of this paper are: nucl-th
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The categories of this paper are: patt-sol
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The categories of this paper are: econ