Evidence map›Paper›PMID 38370342›Full record

ArticleAdvances in knowledge discovery and data mining : ... Pacific-Asia Conference, PAKDD ..., proceedings. Pacific-Asia Conference on Knowledge Discovery and Data Mining2023

MISNN: Multiple Imputation via Semi-parametric Neural Networks.

Zhiqi Bu, Zongyu Dai, Yiliang Zhang, Qi Long

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Advances in knowledge discovery and data mining : ... Pacific-Asia Conference, PAKDD ..., proceedings. Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Zhiqi BuGroups of Applied Mathematics and Computational Science, University of Pennsylvania, Philadelphia, USA.
Zongyu DaiGroups of Applied Mathematics and Computational Science, University of Pennsylvania, Philadelphia, USA.
Yiliang ZhangGroups of Applied Mathematics and Computational Science, University of Pennsylvania, Philadelphia, USA.
Qi LongDepartment of Biostatistics, University of Pennsylvania, Philadelphia, USA.

Funding

Privacy-preserving methods and tools for handling missing data in distributed health data networksR01GM124111 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI LONG, QI · 2017 to 2020
$2.3M
NIGMS NIH HHS R01 GM124111
6 · The paper itself

Abstract

Multiple imputation (MI) has been widely applied to missing value problems in biomedical, social and econometric research, in order to avoid improper inference in the downstream data analysis. In the presence of high-dimensional data, imputation models that include feature selection, especially

Indexed as

ImputationMissing valueSemi-supervised Learning

Identifiers

PMID38370342
PMCPMC10869892

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.