ArticleHeliyon2024
A novel non-invasive embryo evaluation method (NICS-Timelapse) with enhanced predictive precision and clinical impact.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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Who cites it
4 citing papers in PubMed.
- Genetic analysis of biopsy-related droplets in patients undergoing PGT-A and its potential application.Frontiers in endocrinology · 2026Article
- Current progress and open challenges for applying artificial intelligence across thePatterns (New York, N.Y.) · 2025Review
- Predicting pregnancy outcomes in IVF cycles: a systematic review and diagnostic meta- analysis of artificial intelligence in embryo assessment.Contraception and reproductive medicine · 2025Review
- Non-invasive prediction of human embryonic ploidy using artificial intelligence: a systematic review and meta-analysis.EClinicalMedicine · 2024Article
Corrections and comments
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The selection of the finest possible embryo in in-vitro fertilization (IVF) was crucial and revolutionary, particularly when just one embryo is transplanted to lessen the possibility of multiple pregnancies. However, practical usefulness of currently used methodologies may be constrained. Here, we established a novel non-invasive embryo evaluation method that combines non-invasive chromosomal screening (NICS) and Timelapse system along with artificial intelligence algorithms. With an area under the curve (AUC) of 0.94 and an accuracy of 0.88, the NICS-Timelapse model was able to predict blastocyst euploidy. The performance of the model was further evaluated using 75 patients in various clinical settings. The clinical pregnancy and live birth rates of embryos predicted by the NICS-Timelapse model, showing that embryos with higher euploid probabilities were associated with higher clinical pregnancy and live birth rates. These results demonstrated the NICS-Timelapse model's significantly wider application in clinical IVF due to its excellent accuracy and noninvasiveness.
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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.