ReviewFrontiers in reproductive health2025
The integration of artificial intelligence in assisted reproduction: a comprehensive review.
Review in Frontiers in reproductive health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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
13 citing papers in PubMed.
- Contemporary Approaches Towards the Optimization of Embryo Implantation.Journal of clinical medicine · 2026Review
- Review
- Artificial intelligence in infertility treatment: Applications, challenges, and future directions: A narrative review.International journal of reproductive biomedicine · 2026Review
- The potential, perils and pitfalls of Artificial intelligence (AI) in Assisted Reproductive Technologies (ART).Reproductive biology and endocrinology : RB&E · 2026Review
- Artificial Intelligence in Recurrent Pregnancy Loss: Current Evidence, Limitations, and Future Directions.Journal of clinical medicine · 2026Review
- Evolving PCOS Management: From Symptom Control to Phenotype-Targeted Therapy.Diabetes, metabolic syndrome and obesity : targets and therapy · 2026Review
- AI and digital assistive technologies and reproductive rights among women with disabilities in Egypt: a qualitative SWOT study.Frontiers in sociology · 2026Article
- Advanced maternal age and assisted reproductive technologies: outcomes, genomics, and real-world evidence.Frontiers in reproductive health · 2026Review
- Artificial Intelligence in Routine IVF Practice.Biology · 2025Review
- Private equity and reproductive medicine: "Fertile breeding ground" - a physician's perspective".Reproductive biology and endocrinology : RB&E · 2025Review
- Integrating Artificial Intelligence into Perinatal Care Pathways: A Scoping Review of Reviews of Applications, Outcomes, and Equity.Nursing reports (Pavia, Italy) · 2025Review
- AI-driven predictive modelling of orthodontic relapse using retainer compliance and patient factors.Bioinformation · 2025Article
- Comparing AI and physician medical advice quality and humanistic care on social media platforms.Digital healthArticle
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
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence (AI) has emerged as a transformative force in healthcare, with its integration into assisted reproduction technologies representing a notable milestone. The utilization of AI in assisted reproduction is rooted in the persistent challenge of optimizing outcomes. Despite years of progress, success rates in assisted reproductive techniques remain a concern. The current landscape of AI applications demonstrates significant potential to revolutionize various facets of assisted reproduction, including stimulation protocol optimization, embryo formation prediction, oocyte and sperm selection, and live birth prediction from embryos. AI's capacity for precise image-based analysis, leveraging convolutional neural networks, stands out as a promising avenue. Personalized treatment plans and enhanced diagnostic accuracy are central themes explored in this review. AI-driven healthcare products demonstrate the potential for real-time, adaptive health programs, fostering improved communication between patients and healthcare teams. Continuous learning systems to address challenges associated with biased training data and the time required for accurate decision-making capabilities to develop is imperative. Challenges and ethical considerations in AI-assisted conception as evident when taking into consideration issues such as the lack of legislation regulating AI in healthcare, a fact that emphasizes the need for transparency and equity in the development and implementation of AI technologies. The regulatory framework, both in the UK and globally, is making efforts to balance innovation with patient safety. This paper delves into the revolutionary impact of Artificial Intelligence (AI) in the realm of assisted reproduction technologies (ART). As AI continues to evolve, its application in the field of reproductive medicine holds great promise for improving success rates, personalized treatments, and overall efficiency. This comprehensive review explores the current state of AI in assisted reproduction, its potential benefits, challenges, and ethical considerations.
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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.