ReviewJournal of assisted reproduction and genetics2020
Artificial intelligence in the IVF laboratory: overview through the application of different types of algorithms for the classification of reproductive data.
Review in Journal of assisted reproduction and genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 2 of them syntheses that pooled it.
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
49 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Determining risk factors predicting miscarriage among couples undergoing assisted reproductive treatment: a systematic review.BMC pregnancy and childbirth · 2026Pooled it
- AI Tools for Assessing Human Fertility Using Risk Factors: A State-of-the-Art Review.Journal of medical systems · 2023Pooled it
- Automation, Artificial Intelligence (AI), and Digital Management in IVF Laboratories: Current Status, Challenges and Potential.Reproductive sciences (Thousand Oaks, Calif.) · 2026Review
- The Global State of Contemporary Andrology Practice: A Comprehensive Analysis of Clinical Practice, Training Pathways, and Emerging Challenges.The world journal of men's health · 2026Article
- Meat-Borne Bacterial Pathogen Detection: Conventional, Molecular and Emerging AI-Based Strategies.Diagnostics (Basel, Switzerland) · 2026Review
- Study of comparative performance of general-purpose LLM-based systems in predicting IVF outcomes.Journal of assisted reproduction and genetics · 2026Article
- Artificial Intelligence in Routine IVF Practice.Biology · 2025Review
- Enhancing frozen-thawed embryo transfer outcomes and treatment personalization through machine learning models.Journal of assisted reproduction and genetics · 2025Article
- MAIA platform for routine clinical testing: an artificial intelligence embryo selection tool developed to assist embryologists.Scientific reports · 2025Article
- FERTILITY CARE IN LOW- AND MIDDLE- INCOME COUNTRIES: The future use of AI to improve accessibility of assisted reproductive technology in low- and middle-income countries.Reproduction & fertility · 2025Review
- Deep learning classification integrating embryo images with associated clinical information from ART cycles.Scientific reports · 2025Article
- Noninvasive Biomarkers of Human Embryo Developmental Potential.International journal of molecular sciences · 2025Review
- Predictive modeling of pregnancy outcomes utilizing multiple machine learning techniques for in vitro fertilization-embryo transfer.BMC pregnancy and childbirth · 2025Article
- The perception of artificial intelligence and infertility care among patients undergoing fertility treatment.Journal of assisted reproduction and genetics · 2025Article
- Machine learning in predicting infertility treatment success: A systematic literature review of techniques.Journal of education and health promotion · 2025Review
- The integration of artificial intelligence in assisted reproduction: a comprehensive review.Frontiers in reproductive health · 2025Review
- Advanced KPI framework for IVF pregnancy prediction models in IVF protocols.Scientific reports · 2024Article
- Enhancing predictive models for egg donation: time to blastocyst hatching and machine learning insights.Reproductive biology and endocrinology : RB&E · 2024Article
- Harnessing Artificial Intelligence to Predict Ovarian Stimulation Outcomes in In Vitro Fertilization: Scoping Review.Journal of medical Internet research · 2024Article
- Machine learning in time-lapse imaging to differentiate embryos from young vs old mice†.Biology of reproduction · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Over the past years, the assisted reproductive technologies (ARTs) have been accompanied by constant innovations. For instance, intracytoplasmic sperm injection (ICSI), time-lapse monitoring of the embryonic morphokinetics, and PGS are innovative techniques that increased the success of the ART. In the same trend, the use of artificial intelligence (AI) techniques is being intensively researched whether in the embryo or spermatozoa selection. Despite several studies already published, the use of AI within assisted reproduction clinics is not yet a reality. This is largely due to the different AI techniques that are being proposed to be used in the daily routine of the clinics, which causes some uncertainty in their use. To shed light on this complex scenario, this review briefly describes some of the most frequently used AI algorithms, their functionalities, and their potential use. Several databases were analyzed in search of articles where applied artificial intelligence algorithms were used on reproductive data. Our focus was on the classification of embryonic cells and semen samples. Of a total of 124 articles analyzed, 32 were selected for this review. From the proposed algorithms, most have achieved a satisfactory precision, demonstrating the potential of a wide range of AI techniques. However, the evaluation of these studies suggests the need for more standardized research to validate the proposed models and their algorithms. Routine use of AI in assisted reproduction clinics is just a matter of time. However, the choice of AI technique to be used is supported by a better understanding of the principles subjacent to each technique, that is, its robustness, pros, and cons. We provide some current (although incipient) and potential uses of AI on the clinic routine, discussing how accurate and friendly it could be. Finally, we propose some standards for AI research on the selection of the embryo to be transferred and other future hints. For us, the imminence of its use is evident, providing a revolutionary milestone that will impact the ART.
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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.