ArticleCommunications biology2021
Development of deep learning algorithms for predicting blastocyst formation and quality by time-lapse monitoring.
Article in Communications biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 2 of them syntheses that pooled it.
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Who cites it
42 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Deep learning applications for human embryo assessment using time-lapse imaging: scoping review.Frontiers in reproductive health · 2025Pooled it
- Human Oocyte Morphology and Outcomes of Infertility Treatment: a Systematic Review.Reproductive sciences (Thousand Oaks, Calif.) · 2022Pooled it
- From Static to Dynamic: Fluorescence Imaging Technology Advances Precise Embryo Evaluation.Small methods · 2026Review
- AI-enabled precision reproductive medicine: a comprehensive review of clinical applications, decision frameworks, and evidence-based implementation.Journal of assisted reproduction and genetics · 2026Review
- An Optimal Approach in Selecting Embryo for In-Vitro Fertilization (IVF) Based on Deep Learning.Journal of biomedical physics & engineering · 2026Article
- Artificial Intelligence in Embryo Selection: Current Approaches and Clinical Implications.Bioengineering (Basel, Switzerland) · 2026Review
- From genes to germ layers: virtual twins of gastruloids.NPJ systems biology and applications · 2026Review
- Development and validation of deep learning for predicting the growth of ovarian cancer organoids.Chinese medical journal · 2026Article
- YOLO-VML: An Improved Object Detection Model for Blastomeres and Pronuclei Localization in IoMT.IEEE open journal of engineering in medicine and biology · 2026Article
- Safety and efficacy of the automated liquid-phase embryo storage, Hatchferti: a pilot study.PeerJ · 2026Article
- An early prediction model for high-quality blastocyst development based on ANA titer and baseline demographic characteristics in the first IVF/ICSI cycle.Journal of ovarian research · 2025Article
- Predicting pregnancy outcomes in IVF cycles: a systematic review and diagnostic meta- analysis of artificial intelligence in embryo assessment.Contraception and reproductive medicine · 2025Review
- Prediction of blastocyst development using cleavage-stage embryo metrics and maternal age.Scientific reports · 2025Article
- Development and validation of machine learning models for predicting blastocyst yield in IVF cycles.Scientific reports · 2025Article
- Deep learning classification integrating embryo images with associated clinical information from ART cycles.Scientific reports · 2025Article
- The Role of Artificial Intelligence in Female Infertility Diagnosis: An Update.Journal of clinical medicine · 2025Review
- Merging synthetic and real embryo data for advanced AI predictions.Scientific reports · 2025Article
- Combined Input Deep Learning Pipeline for Embryo Selection for In Vitro Fertilization Using Light Microscopic Images and Additional Features.Journal of imaging · 2025Article
- 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
- Advanced KPI framework for IVF pregnancy prediction models in IVF protocols.Scientific reports · 2024Article
Corrections and comments
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Approaches to reliably predict the developmental potential of embryos and select suitable embryos for blastocyst culture are needed. The development of time-lapse monitoring (TLM) and artificial intelligence (AI) may help solve this problem. Here, we report deep learning models that can accurately predict blastocyst formation and usable blastocysts using TLM videos of the embryo's first three days. The DenseNet201 network, focal loss, long short-term memory (LSTM) network and gradient boosting classifier were mainly employed, and video preparation algorithms, spatial stream and temporal stream models were developed into ensemble prediction models called STEM and STEM
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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.