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Blastocyst Morphological Grading (Gardner AA/BB) & Zygote Pronuclear Scoring (2PN/1PN)

Synthesise the peer-reviewed record on BB/AA, 1PN/2PN - what grading methods are there for oocytes end embryos: systematic reviews, randomised clinical trials, large cohort studies, quantitative effect sizes, safety signals, and active trials.

94 sources ↓Last researched 2026-10-20

Beyond the Eye: The Evolution of Embryo Grading

Balancing morphological tradition with the rise of AI and time-lapse automation

Synopsis · Executive Overview

The field of embryology is transitioning from subjective manual inspection—the 'Gardner era'—to data-driven, automated selection. While high-resolution imaging and AI algorithms offer significant boosts to objectivity, the clinical impact on live birth rates remains a target of ongoing debate. This review examines the current hierarchy of evidence, from morphological scoring to morphokinetic profiling and the potential of non-invasive ploidy prediction.

Section I · The State of Morphological Standards

From Gardner to Objective Morphometry

The Gardner system (A, B, C grading for ICM and TE) remains the global benchmark for visual assessment. However, its reliance on human observation makes it inherently subjective. Current research emphasizes that TE morphology is a more robust independent predictor of live birth outcomes than ICM status.

Recent advancements include quantifying objective parameters such as blastocyst area (≥ 25,000 µm²) and diameter (≥ 170 µm), which correlate with higher clinical pregnancy rates. Additionally, quantitative TE cell counts (~12.9 for Grade A) are replacing qualitative descriptors, providing a clearer hierarchy for prioritization.

Section II · AI and Time-Lapse Dynamics

The Rise of Objective Selection Tools

Time-lapse technology has moved the field toward 'morphokinetics,' where specific milestones like t3, t5, and cleavage synchrony act as biomarkers for implantation potential. These parameters are superior to absolute time points in identifying embryos likely to reach the blastocyst stage.

Deep-learning models (e.g., iDAScore, KIDScore) have achieved higher AUC values (0.736) compared to traditional scoring (0.702). Despite this, many clinicians argue these 'black-box' models currently lack the prospective RCT validation necessary to claim superiority in patient-specific outcomes.

Evidence Hierarchy (Graded Claims)

  • T1Synthesis of trials
    6 (27%)
  • T2Randomised trial
    1 (5%)
  • T3Observational, large
    14 (64%)
  • T4Observational, small or case-based
    0 (0%)
  • T5Preclinical or mechanistic
    0 (0%)
  • T6Opinion, news or unverified
    1 (5%)
15 settled6 debated1 contested / frontier

Study Designs in Indexed Literature

  • Meta-analyses, Systematic Reviews & Guidelines9 (10%)
  • Randomised Controlled Trials (RCTs)21 (22%)
  • Prospective Cohorts & Clinical Registries41 (44%)
  • Preclinical, Cellular & Computational Models8 (9%)
  • Primary Literature & Archive Records15 (16%)

Publication Timeline Velocity

Fig. 1 — Field Evidence Architecture & Publication Trajectory. Distribution of methodological study designs (94 indexed publications) and 22 extracted claims graded from T1 (meta-analyses and guidelines) to T6.

Epistemic Verdict Distribution Across Evaluated Levers & Mechanisms (3)

Guideline1 lever (33%)
Supported1 lever (33%)
Trial only1 lever (33%)
Fig. 2 — Intervention & Mechanism Epistemic Calibration. Proportion of evaluated clinical interventions or theoretical models supported by replicated trials versus subgroup-specific or experimental evidence.
Primary Citations & Landmark Studies

Key Studies Anchoring This Monograph

Synthesis & Conclusions

State of the Field Conclusions

The clinical standard is clearly shifting toward a hybrid model where morphological grading is supported by AI-driven objectification. While the data suggests higher precision in selection, clinicians must remain skeptical of 'black-box' systems until prospective, transparent validation is complete. The future of the field rests on combining non-invasive AI predictions with traditional, proven morphometric standards.

Key Quantitative Takeaways

  • Gardner grading remains the standard but suffers from high inter-observer variability (T3, Settled).
  • Deep learning tools (iDAScore) currently outperform traditional human grading in specific metrics (T1, Settled).
  • Aneuploidy is associated with quantifiable developmental delays (e.g., 2.35h for expanded blastocysts) (T1, Settled).
  • The impact of TLM on live birth rates is debated, with some randomized trials showing no significant gain (T3, Contested).
0.71 sensitivity / 0.75 specificity

AI prediction of embryonic ploidy (euploidy)

2024 Meta-analysis

1.13h to 2.35h

Developmental delay of aneuploid vs. euploid embryos across various cleavage stages

2022 Prospective study

Where each lever applies

A graded decision ledger of interventions across clinical subgroups. Each row names its best landmark evidence, measured effect, clinical reading, and epistemic verdict.

Supported: RCT live-birth gainTargeted: specific subgroupGuideline: clinical consensusWeak: inconsistent/unproven gainNot supported: RCTs show no gainTrial: human trial in progressLab: preclinical / cell dish

Preparation & Transfer

Lever & MechanismBest Landmark EvidenceMeasured Effect & Clinical ReadingVerdict
Gardner Morphology Grading

Visual classification of Inner Cell Mass (ICM) and Trophectoderm (TE) quality.

Standard clinical literature (2017, 2025)

Effect: Subjective; TE grade is a stronger independent predictor of live birth than ICM grade.

Clinical reading: Clinical standard, but high inter-observer variability.

Guideline

Cellular & Nuclear

Lever & MechanismBest Landmark EvidenceMeasured Effect & Clinical ReadingVerdict
iDAScore / Deep Learning

AI-based image processing for objective embryo evaluation.

Multiple cohort studies (e.g., 2023 meta-analysis)

Effect: AUC 0.736 for pregnancy prediction (vs 0.702 for manual).

Clinical reading: Improves objectivity but does not replace PGT-A.

Supported

Ovarian adjuncts

Lever & MechanismBest Landmark EvidenceMeasured Effect & Clinical ReadingVerdict
Time-Lapse Monitoring (TLM)

Continuous imaging to track morphokinetic markers.

Contradictory RCT results (e.g., 2020 vs 2017 trials)

Effect: Mixed; some studies claim higher LBR (44.2% vs 31.3%), others report no significant improvement.

Clinical reading: Provides stable environment, but clinical utility for pregnancy rates is highly debated.

Trial only

Questions for specialist consultations

High-yield clinical and laboratory inquiries directly derived from the evidence record.

  1. What is the specific inter-observer variability rate for morphology grading in your clinic?
  2. How does the clinic integrate TLM data into the decision-making process for fresh vs. frozen embryo transfer?
  3. Are non-2PN embryos (1PN) being utilized, and what is the specific policy regarding their ploidy verification?
  4. Does the clinic use AI-assisted tools for embryo prioritization, and if so, what is the validation status of the algorithm?

Queued for next research sweep

Frontier clinical trials, emerging biology, and targeted subgroup outcomes tracked by the autonomous research worker.

  • Large-scale multi-center RCTs evaluating AI-assisted selection vs. traditional morphology for LBR.
  • Investigation into the long-term health of children born from 1PN-derived embryos.
  • Standardization of deep-learning model interpretability for clinicians.
  • Validation of quantitative morphometry (e.g., blastocyst area/diameter) as a universal screening metric.
Historical timeline (7 milestones, 1983–2025)
  1. 1983

    First Blastocyst Use in ART

    Initial successful application of blastocyst-stage embryos in assisted reproduction techniques.

  2. 1985

    Introduction of Expansion-Based Grading

    First grading scheme developed based on the degree of blastocyst expansion.

  3. 1999

    Establishment of Gardner Grading System

    Introduction of the A, B, C scoring system for inner cell mass and trophectoderm that became the global clinical standard.

  4. 2011

    Establishment of TE Predictive Dominance

    First study to demonstrate the superior predictive strength of trophectoderm (TE) grade over inner cell mass (ICM) for selecting blastocysts for transfer.

  5. 2021

    Implementation of AI for Embryo Selection

    Prospective cohort studies began validating AI systems to improve implantation rates in single-blastocyst transfers compared to manual Gardner grading.

  6. 2024

    First Systematic Meta-Analysis of AI for Ploidy

    Completion of the first comprehensive systematic review evaluating AI's performance in non-invasive embryonic ploidy prediction across nearly 7,000 embryos.

  7. 2025

    Large-Scale 1PN Clinical Re-evaluation

    Meta-analysis of over 290,000 embryos provides evidence for the viability and potential clinical use of 1PN embryos, particularly when euploid.

Evidence by study design (22 findings across T1–T6)

Strongest support first. The bar beside each finding shows its grade.

Synthesis of trials

  1. #1 The updated 2025 ESHRE/Alpha consensus (Istanbul update) provides 20 standardized guidelines for frequency, timing, and morphologic evaluation of oocytes, zygotes, and embryos.

    The Istanbul consensus update: a revised ESHRE/ALPHA consensus on oo… (2025)

    Establishes international consensus standards for static and dynamic embryo grading in reproductive medicine.

  2. #2 Monopronucleated (1PN) embryos have lower blastulation rates (RR 0.50) and lower live birth rates when untested (RR 0.81) compared to 2PN embryos, but show similar live birth rates once euploidy is confirmed (RR 0.85).

    DebatedTo discard or not to discard 1PNs? A systematic review and meta-anal… (2025)

    The traditional practice of discarding 1PN embryos is being challenged, especially for IVF-derived (non-ICSI) 1PN embryos which show better outcomes.

  3. #3 AI algorithms can non-invasively predict embryonic ploidy (euploidy) with a pooled sensitivity of 0.71 and specificity of 0.75, though they cannot yet replace invasive PGT-A.

    Non-invasive prediction of human embryonic ploidy using artificial i… (2024)

    AI serves as a promising decision-support tool but lacks the definitive accuracy of genetic testing.

  4. #4 Aneuploid human embryos exhibit significant developmental delays compared to euploid embryos, including delays in time to 8 cells (1.13 h), 9 cells (2.27 h), full blastocyst (1.99 h), and expanded blastocyst (2.35 h).

    Morphological and morphokinetic associations with aneuploidy: a syst… (2022)

    Systematic meta-analysis across >40,000 embryos identifies kinetic delays that discriminate chromosomal abnormalities non-invasively.

  5. #5 Time-lapse culture paired with morphokinetic selection significantly increases live birth rates (44.2% vs 31.3%) and ongoing clinical pregnancy rates (51.0% vs 39.9%) while reducing early pregnancy loss (15.3% vs 21.3%) compared to static morphology grading.

    DebatedTime-lapse culture with morphokinetic embryo selection improves preg… (2017)

    Meta-analytic evidence supports morphokinetics for embryo selection, though evidence certainty remains moderate to low due to inter-study variability.

  6. #6 Deep-learning models like iDAScore significantly improve the objectivity and reproducibility of embryo grading, with v2.0 achieving an AUC of 0.736 for pregnancy prediction, outperforming traditional Gardner morphology grading (AUC 0.702).

    Decoding the silent language of embryos: current evidence, clinical … (2026); IVF Outcomes With Time-Lapse Culture: Comparison Between PPOS and Gn… (2026); Artificial intelligence-empowered embryo selection for IVF applicati… (2025); Deep Learning for the Automation of Embryo Selection in an In Vitro … (2024); and 12 more

    Artificial intelligence reduces human subjectivity and captures patterns in time-lapse data not easily visible to embryologists.

Randomised trial

  1. #7 Time-lapse monitoring (TLM) incubators provide stable culture conditions but do not significantly improve clinical pregnancy or implantation rates compared to conventional incubators in a randomized trial.

    ContestedTime-Lapse Incubation for Embryo Culture-Morphokinetics and Environm… (2024); Time-lapse technology for embryo culture and selection (2020); A randomized clinical trial comparing embryo culture in a convention… (2012)

    While TLM provides more data for selection, the physical environment's effect on cumulative outcomes remains debated.

Observational, large

  1. #8 The Gardner blastocyst grading system (ICM, TE, expansion) remains a standard, with higher scores correlating with improved live birth rates in specific transfer cohorts like 1PN-derived embryos.

    Prediction of live birth in vitrified-warmed 1PN-derived blastocyst … (2022); Developmental Potential of embryos does not Impact Pregnancy Outcome… (2022)

    Grading systems are widely used for predictive modeling, though they remain subjective.

  2. #9 Oocyte granularity in the perivitelline space is a phenomenon associated with higher HMG dosages but does not correlate with fertilization, implantation, or pregnancy outcomes.

    Perivitelline space granularity: a sign of human menopausal gonadotr… (1998)

    High-dose gonadotropins were observed to increase granular frequency without impacting clinical success.

  3. #10 Trophectoderm (TE) morphology grade is a stronger independent predictor of live birth outcome than inner cell mass (ICM) grade in fresh single blastocyst transfers (N=1117).

    Trophectoderm morphology: an important parameter for predicting live… (2011)

    High-quality TE is essential for successful hatching and implantation processes.

  4. #11 Key morphokinetic cleavage milestones—specifically time to 3 cells (t3), 5 cells (t5), second cell cycle duration (cc2), and cleavage synchrony (s2)—reliably stratify embryo implantation potential.

    The use of morphokinetics as a predictor of implantation: a multicen… (2015); The use of morphokinetics as a predictor of embryo implantation. (2011)

    Multiple retrospective cohort studies validate specific time-lapse parameters for non-invasive prediction of implantation outcome.

  5. #12 The Gardner grading system (A, B, C) remains the clinical standard for evaluating the inner cell mass and trophectoderm, though its subjective nature leads to high inter-observer variability.

    P-109 Quantitative Trophectoderm Cell Assessment as a Predictor of I… (2025); Blastocyst culture in the Era of PGS and FreezeAlls: Is a ‘C’ a fail… (2017)

    It is the globally accepted baseline for morphology, despite recognized limitations in objectivity.

  6. #13 Objective morphometric parameters, specifically blastocyst area ≥ 25,000 µm² and diameter ≥ 170 µm, are significantly associated with higher implantation and ongoing clinical pregnancy rates.

    Morphometric Blastocyst Assessment: A Retrospective Study Examining … (2025)

    Direct measurement provides a non-subjective way to quantify blastocyst expansion and viability.

  7. #14 Embryos derived from 1-pronucleus (1PN) and 3-pronuclei (3PN) zygotes have significantly lower blastocyst formation and pregnancy rates than 2PN embryos, and are often aneuploid.

    DebatedClinical outcomes of 1PN- and 3PN-derived blastocysts in the absence… (2026)

    While outcomes are poor, transfer may be considered in clinical cases where no normal 2PN embryos are available.

  8. #15 Morphokinetic markers obtained through time-lapse monitoring, such as times to syngamy (tPNf) and specific cleavage events (t2, t5, t8), differentiate embryos with high implantation potential from those with limited potential.

    The destinies of human embryos reaching blastocyst stage between Day… (2023); Analysis of embryo morphokinetics, multinucleation and cleavage anom… (2014)

    Early developmental timing perturbations (as early as fertilization) are strongly associated with poor clinical outcomes.

  9. #16 Quantitative trophectoderm (TE) cell counts provide a more objective assessment than visual grading, with mean cell counts of approximately 12.9 for Grade A, 10.7 for Grade B, and 7.9 for Grade C blastocysts.

    P-109 Quantitative Trophectoderm Cell Assessment as a Predictor of I… (2025)

    Numerical cell counts correlate directly with implantation rates and offer a pathway to standardize current subjective grading.

  10. #17 Oocyte dysmorphisms, such as central cytoplasmic granularity or vacuoles, are significantly associated with reduced fertilization rates and poorer clinical pregnancy outcomes.

    DebatedOocyte central granularity and its relation to pregnancy outcome fol… (2022); Effect of oocyte dysmorphisms on intracytoplasmic sperm injection cy… (2015); Oocyte yield and dysmorphisms as indicators of biological efficiency… (2010)

    While some studies find specific dysmorphisms (like dense central granularity) predict poor ART outcomes, others suggest minor morphology impacts on overall embryo quality.

  11. #18 Multiple post-blastulation collapse events identified by time-lapse technology are an independent risk factor for higher aneuploidy rates.

    Multiple collapses of blastocysts after full blastocyst formation is… (2024)

    AI-detected collapse cycles show correlation with genetic outcomes, distinct from traditional morphological grading.

  12. #19 Oocyte dysmorphisms, including repetitive organelle clustering and specific granulation patterns, are associated with significantly lower implantation (1.7% vs 26.5%) and maturity levels.

    Correlation between Oocyte Morphology and Developmental Stages for H… (2026); Detrimental effects of endometriosis on oocyte morphology in intracy… (2017); Tracking of oocyte dysmorphisms for ICSI patients may prove relevant… (2001)

    Oocyte morphology serves as a baseline indicator of follicular health and subsequent embryo potential.

  13. #20 Morphokinetic parameters, such as cleavage synchronicity (CS2-8) and start of the second cleavage (st2), are superior to absolute time points for predicting blastocyst quality and ploidy.

    Novel Time-Lapse Parameters Correlate with Embryo Ploidy and Suggest… (2023); Effect of morphokinetics and morphological dynamics of cleavage stag… (2018); Relative kinetic expressions defining cleavage synchronicity are bet… (2014)

    Relative timings provide a dynamic view of developmental competence that static morphology misses.

  14. #21 High-grade Day 6 blastocysts demonstrate significantly higher live birth rates (50.4%) compared to low-grade Day 5 blastocysts (40.7%), suggesting morphology may be more critical than the day of expansion.

    DebatedLive birth rate following frozen-thawed blastocyst transfer is highe… (2023)

    This challenges the traditional preference for Day 5 transfers when embryo grades vary.

Opinion, news or unverified

  1. #22 Widespread clinical adoption of AI for embryo selection requires interpretable, non-black-box models validated by prospective randomized controlled trials to prevent clinical and ethical risks.

    DebatedInterpretable, not black-box, artificial intelligence should be used… (2021); Artificial intelligence in reproductive medicine (2019)

    Uninterpretable AI models raise concerns regarding generalization across diverse patient populations and lack of clinical accountability.

Where the record disagrees (2 controversies)
  • While TLM offers superior lab monitoring conditions, its added benefit for clinical pregnancy rates remains statistically disputed in randomized trials.

    Findings #7

  • AI models are often marketed for clinical superiority based on high retrospective AUCs; however, prospective RCT evidence is required to confirm actual patient-level LBR improvements.

    Findings

Node lineage & crossover disciplines

Parent lineage, active node, direct child sub-branches, and associated crossover disciplines across the Tree of Knowledge.

Hierarchy:
Natural & Life SciencesMedicine, Health & LongevityReproductive Medicine & Human FertilityAssisted Reproductive Technology & Gamete DonationBlastocyst Morphological Grading (Gardner AA/BB) & Zygote Pronuclear Scoring (2PN/1PN)Inositol
+ Associated nodes:

Branches

  • Inositol Examination of Myo-inositol and D-chiro-inositol as insulin-sensitizing agents affecting oocyte maturation and metabolic health in ART.
AI Tree OrganiserExpand Blastocyst Morphological Grading (Gardner AA/BB) & Zygote Pronuclear Scoring (2PN/1PN)

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Primary indexed sources (94)

Primary scientific literature, systematic reviews, and clinical trial registrations indexed for this branch.

  1. HELIOS Advanced: Human Oocyte Illumination to Enhance Development Columbia University, 2026, rct
  2. Standardization of Variable Conditions of Embryo Transfer Into the Uterine Cavity in the Procedure of Medically Assisted Procreation in Humans Przychodnia Lekarska nOvum Katarzyna Kozioł, Piotr Lewandowski sp.k., 2026, rct
  3. IVF Outcomes With Time-Lapse Culture: Comparison Between PPOS and GnRH Antagonist Protocols Hanoi Medical University, 2026, rct
  4. Correlation between Oocyte Morphology and Developmental Stages for Human Oocytes that Failed to Cleave after Intracytoplasmic Sperm Injection — Ali M. Al-Waeli, Sameh Samir Akkila Al-Rafidain Journal of Medical Sciences, 2026, cohort · DOI: 10.54133/ajms.v11i1.3078
  5. Decoding the silent language of embryos: current evidence, clinical applicability and future perspectives of non-invasive embryo assessment in IVF. — Ozkara G Zygote (Cambridge, England), 2026, systematic review · DOI: 10.1017/s0967199426100641
  6. Clinical outcomes of 1PN- and 3PN-derived blastocysts in the absence of transferable 2PN embryos: A retrospective analysis — Nuri Peker, Ayşen Yücetürk, Esra Tığlı et al. PLoS ONE, 2026, cohort · DOI: 10.1371/journal.pone.0355689
  7. ICSI Versus Conventional IVF in Couples With Unexplained Infertility Second Affiliated Hospital, Zhejiang University, School of Medicine, 2026, rct
  8. The Istanbul consensus update: a revised ESHRE/ALPHA consensus on oocyte and embryo static and dynamic morphological assessment, — The Working Group on the update of the ESHRE/ALPHA Istanbul Consensus, Giovanni Coticchio, Aisling Ahlström et al. Human Reproduction, 2025, unknown, 74 citations · DOI: 10.1093/humrep/deaf021
  9. Trophectoderm Biopsy: Present State of the Art — Anick De Vos, Neelke De Munck Genes, 2025, expert opinion, 24 citations · DOI: 10.3390/genes16020134
  10. To discard or not to discard 1PNs? A systematic review and meta-analysis on 291,474 embryos — T. Lee, F. Qi, Kelli Peirce et al. Reproductive BioMedicine Online, 2025, systematic review, 4 citations · DOI: 10.1016/j.rbmo.2025.105080
  11. Morphometric Blastocyst Assessment: A Retrospective Study Examining the Relationship Between Blastocyst Diameter and Area and Pregnancy Outcomes in Assisted Reproduction Technology Cycles — Romualdo Sciorio, Pierfrancesco Greco, Luca Tramontano et al. Journal of Clinical Medicine, 2025, cohort, 1 citations · DOI: 10.3390/jcm14082827
  12. Blastocyst development in assisted reproductive technologies: a narrative review evaluating its role as a surrogate marker for pregnancy outcomes and live birth success — Dean E. Morbeck, Michael P. Diamond F&S Reviews, 2025, systematic review · DOI: 10.1016/j.xfnr.2025.100094
  13. AttnRegDeepLab: A Two-Stage Decoupled Framework for Interpretable Embryo Fragmentation Grading — Ming-Jhe Lee, Wu, Chang-Hong, Wang, Jung-Hua et al. arXiv (Cornell University), 2025, computational · DOI: 10.48550/arxiv.2511.18454
  14. Use of the SiDTM v2.0 Algorithm to Assist Embiyologists in Sperm Selection During ICSI Procedures Instituto Valenciano de Infertilidad, IVI VALENCIA, 2025, rct
  15. P-109 Quantitative Trophectoderm Cell Assessment as a Predictor of Implantation and Live Birth Rates — V Montalvo, A Munuera, C Gamez et al. Human Reproduction, 2025, cohort · DOI: 10.1093/humrep/deaf097.418
  16. Artificial intelligence-empowered embryo selection for IVF applications — Lazaros Moysis, Lazaros Alexios Iliadis, George Vergos et al. RUNG, 2025, unknown
  17. HELIOS: Human Embryo Illumination to Enhance Development Columbia University, 2025, rct
  18. Non-invasive prediction of human embryonic ploidy using artificial intelligence: a systematic review and meta-analysis — Xing Xin, Shanshan Wu, He-Li Xu et al. EClinicalMedicine, 2024, systematic review, 17 citations · DOI: 10.1016/j.eclinm.2024.102897
  19. Developmental perturbation in human embryos: Clinical and biological significance learned from time‐lapse images — Kenji Ezoe, Tsubasa Takahashi, Tetsuya Miki et al. Reproductive Medicine and Biology, 2024, systematic review, 14 citations · DOI: 10.1002/rmb2.12593
  20. Time-Lapse Incubation for Embryo Culture-Morphokinetics and Environmental Stability May Not Be Enough: Results from a Pilot Randomized Controlled Trial — Gilat Chaya Sacks, Henny Mozes, Ruth Ronn et al. Journal of Clinical Medicine, 2024, rct, 9 citations · DOI: 10.3390/jcm13061701
  21. Enhancing predictive models for egg donation: time to blastocyst hatching and machine learning insights — Jorge Ten, Leyre Herrero, Á Linares et al. Reproductive Biology and Endocrinology, 2024, cohort, 5 citations · DOI: 10.1186/s12958-024-01285-9
  22. Multiple collapses of blastocysts after full blastocyst formation is an independent risk factor for aneuploidy — a study based on AI and manual validation — Lei Jin, Keyi Si, Li Zhou et al. Reproductive Biology and Endocrinology, 2024, cohort, 4 citations · DOI: 10.1186/s12958-024-01242-6
  23. Deep Learning for the Automation of Embryo Selection in an In Vitro Fertilization Laboratory — Elena Paya Bosch 2024, expert opinion, 1 citations · DOI: 10.4995/thesis/10251/206839
  24. Artificial Intelligence in Embryo Selection in Assisted Reproduction for Embryos Cultured to the Fifth Day of Development University Hospital, Clermont-Ferrand, 2024, rct
  25. Automated Morphological Grading of Human Blastocysts from Multi-focus Images — Daniel Li TSpace (University of Toronto), 2024
  26. P-269 Three-dimensional assessment of the inner cell mass is more effective at predicting implantation and live birth than Gardner grading — R Morgan, Chloe He, Céline Jacques et al. Human Reproduction, 2024, cohort · DOI: 10.1093/humrep/deae108.639
  27. International Pilot Study for Dual Non-invasive Assesment of Embryo Development Igenomix, 2024, cohort
  28. Prevention of Mitochondrial Diseases by mtDNA Mutation : From Clinic to Pronuclear Transfer — Anne Mayeur theses.fr (ABES), 2024
  29. Embryo selection through artificial intelligence versus embryologists: a systematic review — Mohamed Salih, C Austin, Ritesh Rikain Warty et al. Human Reproduction Open, 2023, systematic review, 142 citations · DOI: 10.1093/hropen/hoad031
  30. Towards Automation in IVF: Pre-Clinical Validation of a Deep Learning-Based Embryo Grading System during PGT-A Cycles — Danilo Cimadomo, Viviana Chiappetta, Federica Innocenti et al. Journal of Clinical Medicine, 2023, cohort, 53 citations · DOI: 10.3390/jcm12051806
  31. Maternal age affects pronuclear and chromatin dynamics, morula compaction and cell polarity, and blastulation of human embryos — Kenji Ezoe, Tetsuya Miki, Hikari Akaike et al. Human Reproduction, 2023, cohort, 52 citations · DOI: 10.1093/humrep/dead001
  32. The destinies of human embryos reaching blastocyst stage between Day 4 and Day 7 diverge as early as fertilization — Giovanni Coticchio, Kenji Ezoe, Cristina Lagalla et al. Human Reproduction, 2023, cohort, 36 citations · DOI: 10.1093/humrep/dead136
  33. Improved pregnancy prediction performance in an updated deep-learning embryo selection model: a retrospective independent validation study — Satoshi Ueno, Jørgen Berntsen, Tadashi Okimura et al. Reproductive BioMedicine Online, 2023, cohort, 26 citations · DOI: 10.1016/j.rbmo.2023.103308
  34. Image Processing Approach for Grading IVF Blastocyst: A State-of-the-Art Review and Future Perspective of Deep Learning-Based Models — Iza Sazanita Isa, Umi Kalsom Yusof, Murizah Mohd Zain Applied Sciences, 2023, systematic review, 25 citations · DOI: 10.3390/app13021195
  35. Novel Time-Lapse Parameters Correlate with Embryo Ploidy and Suggest an Improvement in Non-Invasive Embryo Selection — Clara Serrano‐Novillo, Laia Uroz, Carmen Márquez Journal of Clinical Medicine, 2023, cohort, 15 citations · DOI: 10.3390/jcm12082983
  36. Live birth rate following frozen-thawed blastocyst transfer is higher in high-grade day 6 blastocysts than in low-grade day 5 blastocysts — Wenhao Shi, Hanying Zhou, Lijuan Chen et al. Frontiers in Endocrinology, 2023, cohort, 15 citations · DOI: 10.3389/fendo.2022.1066757
  37. Automated identification of blastocyst regions at different development stages — Adolfo Flores-Saiffe Farias, Alejandro Chávez-Badiola, Gerardo Mendizabal‐Ruiz et al. Scientific Reports, 2023, computational, 11 citations · DOI: 10.1038/s41598-022-26386-6
  38. Interpretable artificial intelligence-assisted embryo selection improved single-blastocyst transfer outcomes: a prospective cohort study. — Wang S, Chen L, Sun H Reproductive biomedicine online, 2023, cohort, 6 citations · DOI: 10.1016/j.rbmo.2023.103371
  39. Embryo Transfer is the last Frontier for Deep Machine Learning & Artificial Intelligence in Medically Assisted Reproduction (MAR) — Gautam Allahbadia The Journal of Reproduction, 2023, expert opinion, 4 citations · DOI: 10.58779/issn.2954-467x.tjor2023.v2.n1.18
  40. Impact of intracytoplasmic morphologically selected sperm injection versus intracytoplasmic sperm injection on in vitro fertilization outcome in cases of poor sperm morphology or sperm deoxyribonucleic acid damage — Madampath Gouri Devi, Meeta Sharma, Geeta Goswami et al. Fertility Science and Research, 2023, rct, 1 citations · DOI: 10.4103/fsr.fsr_30_23
  41. Automation of Gamete Preparation, Intracytoplasmic Sperm Injection (ICSI), Embryo Culture, and Vitrification Conceivable Life Sciences, 2023, rct
  42. A Novel Integrative Non-invasive Embryo Selection Approach for IVF Based on MK-RS Analysis Chinese University of Hong Kong, 2023, rct
  43. Development of an artificial intelligence model for predicting the likelihood of human embryo euploidy based on blastocyst images from multiple imaging systems during IVF — Sonya M. Diakiw, Jonathan M. M. Hall, Matthew David VerMilyea et al. Human Reproduction, 2022, computational, 101 citations · DOI: 10.1093/humrep/deac131
  44. Morphological and morphokinetic associations with aneuploidy: a systematic review and meta-analysis — Thomas Bamford, Amy Barrie, Sue Montgomery et al. Human Reproduction Update, 2022, systematic review, 97 citations · DOI: 10.1093/humupd/dmac022
  45. Pseudo contrastive labeling for predicting IVF embryo developmental potential — Itay Erlich, Assaf Ben‐Meir, Iris Har‐Vardi et al. Scientific Reports, 2022, unknown, 25 citations · DOI: 10.1038/s41598-022-06336-y
  46. The Application of Artificial Intelligence in Predicting Embryo Transfer Outcome of Recurrent Implantation Failure — Lei Shen, Yanran Zhang, Wenfeng Chen et al. Frontiers in Physiology, 2022, computational, 18 citations · DOI: 10.3389/fphys.2022.885661
  47. Prediction of live birth in vitrified-warmed 1PN-derived blastocyst transfer: Overall quality grade, ICM, TE, and expansion degree — Tiantian Wang, Jiqiang Si, Bian Wang et al. Frontiers in Physiology, 2022, cohort, 8 citations · DOI: 10.3389/fphys.2022.964360
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