Evidence map›Paper›PMID 36362775›Full record

ArticleJournal of clinical medicine2022

Rupture Prediction for Microscopic Oocyte Images of Piezo Intracytoplasmic Sperm Injection by Principal Component Analysis.

Naomi Yagi, Hyodo Tsuji, Takashi Morimoto, Tomohiro Maekawa, Shimpei Mizuta, Tomomoto Ishikawa, Yutaka Hata

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2022. 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
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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

7 authors.

Naomi YagiAdvanced Medical Engineering Research Institute, University of Hyogo, Himeji 670-0836, Japan.ORCID 0000-0002-2435-6509
Hyodo TsujiSchool of Engineering, University of Hyogo, Himeji 671-2280, Japan.
Takashi MorimotoReproduction Clinic Tokyo, Tokyo 105-7103, Japan.
Tomohiro MaekawaReproduction Clinic Tokyo, Tokyo 105-7103, Japan.
Shimpei MizutaReproduction Clinic Tokyo, Tokyo 105-7103, Japan.
Tomomoto IshikawaReproduction Clinic Tokyo, Tokyo 105-7103, Japan.
Yutaka HataGraduate School of Information Science, University of Hyogo, Kobe 650-0047, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Assisted reproductive technology (ART) has progressed rapidly, resulting in a great improvement in the clinical pregnancy ratio. When applying the protocol of piezo intracytoplasmic sperm injection (Piezo-ICSI), it is very important to puncture the zona pellucida and the oocyte cytoplasmic membrane without rupturing the oocyte cytoplasmic membrane. Previous studies have shown that the poor extensibility of the oocyte cytoplasmic membrane might be closely related to rupture. However, no consensus has been reached regarding how the quality of the oocyte for extensible ability or rupture possibility affects the surfaces of the oocyte on the microscopic frames. We conducted this study to provide evidence that artificial intelligence (AI) techniques are superior for predicting the tendency of oocyte rupture before puncturing on Piezo-ICSI. To inspect it, we provided a retrospective trial of 38 rupture oocytes and 55 nonruptured oocytes. This study marked the highest accuracy of 91.4% for predicting oocytes rupture using the support-vector machine method of machine learning. We conclude that AI technologies might serve an important role and provide a significant benefit to ART.

Indexed as

oocytePiezo-ICSIprincipal component analysisrupturesupport-vector machine

Identifiers

PMID36362775
PMCPMC9659053

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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.