Evidence map›Paper›PMID 34354339›Full record

ArticleINFORMS journal on computing2021

Supervised t-distributed stochastic neighbor embedding for data visualization and classification.

Yichen Cheng, Xinlei Wang, Yusen Xia

Open access · greenAbstract read
In one paragraph

Article in INFORMS journal on computing, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
0.7field-weighted citation impact, top 28% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 22 citations in OpenAlex.

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  6. Structure preserving t-SNE of matrix framed data.Computational and structural biotechnology journal · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Yichen ChengInstitute for Insights, Georgia State University, 35 Broad St. NW, Atlanta, GA 30303.
Xinlei WangDepartment of Statistical Science, South Methodist University, 102 Heroy Science Hall, 3225 Daniel Avenue, Dallas, TX 75275.
Yusen XiaInstitute for Insights, Georgia State University, 35 Broad St. NW, Atlanta, GA 30303.
Georgia State University · USSouthern Methodist University · US

Funding

Normalizing Gene Expression Data from Formalin-Fixed Paraffin-Embedded SamplesR15GM131390 · NIGMS · SOUTHERN METHODIST UNIVERSITY · PI WANG, XINLEI · 2019 to 2019
$432k
NIGMS NIH HHS R15 GM131390
6 · The paper itself

Abstract

We propose a novel supervised dimension reduction method, called supervised t-distributed stochastic neighbor embedding (St-SNE), which achieves dimension reduction by preserving the similarities of data points in both feature and outcome spaces. The proposed method can be used for both prediction and visualization tasks, with the ability to handle high-dimensional data. We show through a variety of datasets that when compared with a comprehensive list of existing methods, St-SNE has superior prediction performance in the ultra-high dimensional setting where the number of features

Indexed as

classificationdimension size estimationsupervised dimension reductionultra-high dimensionvisualization

Identifiers

PMID34354339
PMCPMC8330414
OpenAlexW3084621683

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.