Evidence map›Paper›PMID 33211025›Full record

ArticleJMIR medical informatics2020

Web- and Artificial Intelligence-Based Image Recognition For Sperm Motility Analysis: Verification Study.

Vincent Fs Tsai, Bin Zhuang, Yuan-Hung Pong, Ju-Ton Hsieh, Hong-Chiang Chang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in JMIR medical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
3.2field-weighted citation impact, top 8% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.

  1. Pooled it
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  3. [Advances in the Application of Artificial Intelligence in the Field of Male Infertility].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Vincent Fs TsaiDepartment of Urology, Ten-Chan General Hospital, Taoyuan, Taiwan.ORCID https://orcid.org/0000-0002-8274-2344
Bin ZhuangDivision of Research and Development, Createcare Technology Corporation, Shenzhen, China.ORCID https://orcid.org/0000-0001-9638-2784
Yuan-Hung PongDepartment of Urology, National Taiwan University Hospital, Taipei, Taiwan.ORCID https://orcid.org/0000-0001-7319-7834
Ju-Ton HsiehDepartment of Urology, National Taiwan University Hospital, Taipei, Taiwan.ORCID https://orcid.org/0000-0001-7545-8487
Hong-Chiang ChangDepartment of Urology, National Taiwan University Hospital, Taipei, Taiwan.ORCID https://orcid.org/0000-0001-5411-6680
National Taiwan University Hospital · TWTen Chen Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHuman sperm quality fluctuates over time. Therefore, it is crucial for couples preparing for natural pregnancy to monitor sperm motility.

objectiveThis study verified the performance of an artificial intelligence-based image recognition and cloud computing sperm motility testing system (Bemaner, Createcare) composed of microscope and microfluidic modules and designed to adapt to different types of smartphones.

methodsSperm videos were captured and uploaded to the cloud with an app. Analysis of sperm motility was performed by an artificial intelligence-based image recognition algorithm then results were displayed. According to the number of motile sperm in the vision field, 47 (deidentified) videos of sperm were scored using 6 grades (0-5) by a male-fertility expert with 10 years of experience. Pearson product-moment correlation was calculated between the grades and the results (concentration of total sperm, concentration of motile sperm, and motility percentage) computed by the system.

resultsGood correlation was demonstrated between the grades and results computed by the system for concentration of total sperm (r=0.65, P<.001), concentration of motile sperm (r=0.84, P<.001), and motility percentage (r=0.90, P<.001).

conclusionsThis smartphone-based sperm motility test (Bemaner) accurately measures motility-related parameters and could potentially be applied toward the following fields: male infertility detection, sperm quality test during preparation for pregnancy, and infertility treatment monitoring. With frequent at-home testing, more data can be collected to help make clinical decisions and to conduct epidemiological research.

Indexed as

artificial intelligencecloud computinghome sperm testMale infertilitysemen analysissmartphonetelemedicine

Identifiers

PMID33211025
PMCPMC7714652
OpenAlexW3097796286

What OpenQuestion holds

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LicenceCC BY
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.