ArticleJournal of assisted reproduction and genetics2021
End-to-end deep learning for recognition of ploidy status using time-lapse videos.
Article in Journal of assisted reproduction and genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06762704 (A Non-Invasive Artificial Intelligence Model for the Prediction of Human Blastocyst Ploidy), which is not on this map. Cited by 25 papers, 1 of them a synthesis that pooled it.
What it found
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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.
A Non-Invasive Artificial Intelligence Model for the Prediction of Human Blastocyst Ploidy: a Multi-Center, Prospective, Non-Randomized Validation Study
Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Deep learning applications for human embryo assessment using time-lapse imaging: scoping review.Frontiers in reproductive health · 2025Pooled it
- Current state of artificial intelligence applications in assisted reproductive technology: A narrative review.Clinical and experimental reproductive medicine · 2026Article
- Current progress and open challenges for applying artificial intelligence across thePatterns (New York, N.Y.) · 2025Review
- Time-Lapse Imaging in IVF: Bridging the Gap Between Promises and Clinical Realities.International journal of molecular sciences · 2025Review
- Personalized prediction model for miscarriage: in-depth sperm DNA fragmentation.Journal of assisted reproduction and genetics · 2025Article
- Application of a methodological framework for the development and multicenter validation of reliable artificial intelligence in embryo evaluation.Reproductive biology and endocrinology : RB&E · 2025Article
- Large language models to facilitate pregnancy prediction after in vitro fertilization.Acta obstetricia et gynecologica Scandinavica · 2025Article
- Review
- Artificial Intelligence, Clinical Decision Support Algorithms, Mathematical Models, Calculators Applications in Infertility: Systematic Review and Hands-On Digital Applications.Mayo Clinic proceedings. Digital health · 2024Review
- Non-invasive prediction of human embryonic ploidy using artificial intelligence: a systematic review and meta-analysis.EClinicalMedicine · 2024Article
- Non-invasively predicting euploidy in human blastocysts via quantitative 3D morphology measurement: a retrospective cohort study.Reproductive biology and endocrinology : RB&E · 2024Article
- Automatic ploidy prediction and quality assessment of human blastocysts using time-lapse imaging.Nature communications · 2024Article
- Leveraging federated learning for boosting data privacy and performance in IVF embryo selection.Journal of assisted reproduction and genetics · 2024Article
- Generative artificial intelligence to produce high-fidelity blastocyst-stage embryo images.Human reproduction (Oxford, England) · 2024Article
- WISE: whole-scenario embryo identification using self-supervised learning encoder in IVF.Journal of assisted reproduction and genetics · 2024Article
- Improved prediction of clinical pregnancy using artificial intelligence with enhanced inner cell mass and trophectoderm images.Scientific reports · 2024Article
- Artificial intelligence in time-lapse system: advances, applications, and future perspectives in reproductive medicine.Journal of assisted reproduction and genetics · 2024Review
- An artificial intelligence algorithm to select most viable embryos considering current process in IVF labs.Frontiers in artificial intelligence · 2024Article
- Deep learning pipeline reveals key moments in human embryonic development predictive of live birth after in vitro fertilization.Biology methods & protocols · 2024Article
- Morphokinetic parameters of mouse oocyte meiotic maturation and cumulus expansion are not affected by reproductive age or ploidy status.Journal of assisted reproduction and genetics · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeOur retrospective study is to investigate an end-to-end deep learning model in identifying ploidy status through raw time-lapse video.
methodsBy randomly dividing the dataset of time-lapse videos with known outcome of preimplantation genetic testing for aneuploidy (PGT-A), a deep learning model on raw videos was trained by the 80% dataset, and used to test the remaining 20%, by feeding time-lapse videos as input and the PGT-A prediction as output. The performance was measured by an average area under the curve (AUC) of the receiver operating characteristic curve. RESULT(S): With 690 sets of time-lapse video image, combined with PGT-A results, our deep learning model has achieved an AUC of 0.74 from the test dataset (138 videos), in discriminating between aneuploid embryos (group 1) and others (group 2, including euploid and mosaic embryos).
conclusionOur model demonstrated a proof of concept and potential in recognizing the ploidy status of tested embryos. A larger scale and further optimization on the exclusion criteria would be included in our future investigation, as well as prospective approach.
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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.