Evidence map›Paper›PMID 31164207›Full record

ArticleArtificial intelligence in medicine2019

Sparse support vector machines with L

Zhenqiu Liu, David Elashoff, Steven Piantadosi

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Artificial intelligence in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Zhenqiu LiuDepartment of Public Health Sciences, Penn State College of Medicine, Hershey, PA 17033, USA. Electronic address: zliu@phs.psu.edu.
David ElashoffDepartment of Medicine, University of California at Los Angeles, CA 90024, USA.
Steven PiantadosiSamuel Oschin Cancer Center, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.

Funding

UCLA Clinical Translational Science InstituteUL1TR001881 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ARLEEN F. BROWN, ARASH NAEIM · 2016 to 2026
$118.1M
Using polygenic scores to enhance both variant discovery, and understanding of functional consequences of genetic variation in IBD.P01DK046763 · NIDDK · CEDARS-SINAI MEDICAL CENTER · PI TARGAN, STEPHAN R. · 1992 to 2020
$31.1M
Prostate Cancer Bone Metastasis: Biology and TargetingP01CA098912 · NCI · EMORY UNIVERSITY · PI ZAYZAFOON, MAJD · 2003 to 2019
$24.0M
NCATS NIH HHS UL1 TR001881NCI NIH HHS P01 CA098912NIDDK NIH HHS P01 DK046763
6 · The paper itself

Abstract

Omics data usually have ultra-high dimension (p) and small sample size (n). Standard support vector machines (SVMs), which minimize the L

Indexed as

Gene ExpressionSupport Vector MachineArtificial IntelligenceHumansMetagenomicsClassificationFeature selectionL(0) approximationMetagenomics sequencingSVMUltra-high dimensional data

Identifiers

PMID31164207
PMCPMC6553498

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.