Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Contrastive Learning of Single-Cell Phenotypic Representations for
  Treatment Classification   Learning robust representations to discriminate cell phenotypes based on
microscopy images is important for drug discovery. Drug development efforts
typically analyse thousands of cell images to screen for potential treatments.
Early works focus on creating hand-engineered features from these images or
learn such features with deep neural networks in a fully or weakly-supervised
framework. Both require prior knowledge or labelled datasets. Therefore,
subsequent works propose unsupervised approaches based on generative models to
learn these representations. Recently, representations learned with
self-supervised contrastive loss-based methods have yielded state-of-the-art
results on various imaging tasks compared to earlier unsupervised approaches.
In this work, we leverage a contrastive learning framework to learn appropriate
representations from single-cell fluorescent microscopy images for the task of
Mechanism-of-Action classification. The proposed work is evaluated on the
annotated BBBC021 dataset, and we obtain state-of-the-art results in NSC, NCSB
and drop metrics for an unsupervised approach. We observe an improvement of 10%
in NCSB accuracy and 11% in NSC-NSCB drop over the previously best unsupervised
method. Moreover, the performance of our unsupervised approach ties with the
best supervised approach. Additionally, we observe that our framework performs
well even without post-processing, unlike earlier methods. With this, we
conclude that one can learn robust cell representations with contrastive
learning.

21
The categories of this paper are: adap-org
35
The categories of this paper are: mtrl-th
28
The categories of this paper are: alg-geom
27
The categories of this paper are: comp-gas
12
The categories of this paper are: nucl-th
20
The categories of this paper are: acc-phys
33
The categories of this paper are: plasm-ph
22
The categories of this paper are: chao-dyn
29
The categories of this paper are: funct-an
24
The categories of this paper are: dg-ga
37
The categories of this paper are: supr-con
31
The categories of this paper are: ao-sci
23
The categories of this paper are: solv-int
15
The categories of this paper are: nucl-ex
0
The categories of this paper are: hep-ph
7
The categories of this paper are: hep-th