ReviewSichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition2024
[Application of Artificial Intelligence in Sperm Quality Analysis and Sperm Screening].
Review in Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Cautionary lessons from real-world testing of GPT-4.1 AI for pediatric foreign body aspiration.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Infertility is a global health issue, and more and more people are hoping to have babies by means of assisted reproductive technology. However, there are still many challenges in fertilization and pregnancy outcomes. Sperm quality is a key factor affecting the success rate of assisted reproduction. Therefore, sperm quality screening is crucial for achieving breakthroughs in assisted reproduction technology. At present, with its capabilities in the field of image recognition, artificial intelligence (AI) is providing new ideas and methods for sperm screening. Various attempts have been made with AI-based models to evaluate indicators such as sperm morphology, DNA quality, and motility level, and some results have been achieved. Herein, we reviewed the application of AI in sperm quality analysis and selection, providing support for the future development of AI and the improvement in the fertilization rate and outcomes of assisted reproductive technology.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.