Evidence map›Paper›PMID 35233348›Full record

ArticleProceedings of the ... European Signal Processing Conference (EUSIPCO). EUSIPCO (Conference)2021

Unsupervised Detection of Anomalies in Fetal Heart Rate Tracings using Phase Space Reconstruction.

Liu Yang, Marzieh Ajirak, Cassandra Heiselman, J Gerald Quirk, Petar M Djurić

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings of the ... European Signal Processing Conference (EUSIPCO). EUSIPCO (Conference), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. UNSUPERVISED CLUSTERING AND ANALYSIS OF CONTRACTION-DEPENDENT FETAL HEART RATE SEGMENTS.Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP (Conference) · 2022
    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

5 authors.

Liu YangDepartment of Electrical and Computer Engineering, Stony Brook University.
Marzieh AjirakDepartment of Electrical and Computer Engineering, Stony Brook University.
Cassandra HeiselmanDepartment of Obstetrics, Gynecology and Reproductive Medicine, Stony Brook University Stony Brook, NY 11794, USA.
J Gerald QuirkDepartment of Obstetrics, Gynecology and Reproductive Medicine, Stony Brook University Stony Brook, NY 11794, USA.
Petar M DjurićDepartment of Electrical and Computer Engineering, Stony Brook University.

Funding

Rethinking Electronic Fetal Monitoring to Improve Perinatal Outcomes and Reduce Frequency of Operative Vaginal and Cesarean DeliveriesR01HD097188 · NICHD · STATE UNIVERSITY NEW YORK STONY BROOK · PI DJURIC, PETAR M, QUIRK, J GERALD · 2019 to 2023
$3.2M
NICHD NIH HHS R01 HD097188
6 · The paper itself

Abstract

Detection of anomalies in time series is still a challenging problem. In this paper, we provide a new approach to unsupervised detection of anomalies in time series based on the concept of phase space reconstruction and manifolds. We propose a rotation-insensitive metric for quantifying the similarity of manifolds and a method that uses it for estimating the probability of an outlier. The proposed method does not rely on any features and can be used for signals with variable lengths. We tested it on both synthetic signals and real fetal heart rate tracings. The method has promising performance and can be used for interpreting the severity of fetal asphyxia.

Identifiers

PMID35233348
PMCPMC8884191

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Registered trials

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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.