ReviewReproduction (Cambridge, England)2019
Artificial intelligence in reproductive medicine.
Review in Reproduction (Cambridge, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 102 papers, 3 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
102 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Investigating the role of artificial intelligence in the diagnosis and prediction of endometriosis using ultrasound images: a systematic review.Reproductive health · 2026Pooled it
- AI Tools for Assessing Human Fertility Using Risk Factors: A State-of-the-Art Review.Journal of medical systems · 2023Pooled it
- Social Freezing: Pressing Pause on Fertility.International journal of environmental research and public health · 2021Pooled it
- Optimizing oocyte yield utilizing a machine learning model for dose and trigger decisions, a multi-center, prospective study.Scientific reports · 2024Trial
- Interobserver Agreement Between Artificial Intelligence, Radiologist, and Gynecologist in Hysterosalpingography Interpretation: A Retrospective Comparative Study.Diagnostics (Basel, Switzerland) · 2026Article
- A machine learning-based score to predict live birth after mosaic embryo transfer.Journal of assisted reproduction and genetics · 2026Observational
- Multimodal ultrasound assessment of ovarian reserve.Abdominal radiology (New York) · 2026Review
- Observational
- Artificial intelligence-driven precision treatment of reproductive medicine-related diseases: the optimal protocol choice for IVF-ET.Journal of advanced research · 2026Article
- Artificial intelligence in infertility treatment: Applications, challenges, and future directions: A narrative review.International journal of reproductive biomedicine · 2026Review
- Then and Now: What We Have Learned From the WHI.The Journal of clinical endocrinology and metabolism · 2026Review
- Study of comparative performance of general-purpose LLM-based systems in predicting IVF outcomes.Journal of assisted reproduction and genetics · 2026Article
- Smart Kiosk for Nutritional Management of People With Diabetes in Underserved Communities: Development and Technical Evaluation.JMIR formative research · 2026Article
- Benchmarking large language models for predictive modeling in biomedical research with a focus on reproductive health.Cell reports. Medicine · 2026Article
- Artificial Intelligence in Recurrent Pregnancy Loss: Current Evidence, Limitations, and Future Directions.Journal of clinical medicine · 2026Review
- Reproductive Longevity: Innovative Approaches Beyond Hormone Replacement Therapy.Medicina (Kaunas, Lithuania) · 2026Review
- Canthaxanthin enhances the quality of cryopreserved goat spermatozoa.Veterinary research forum : an international quarterly journal · 2026Article
- Endometrial immune dysregulation shapes CD8Frontiers in immunology · 2026Article
- TongueNet-GYN: a multimodal deep learning framework for non-invasive gynecological disease screening in digital public health.Frontiers in public health · 2026Article
- Current Insights into Endometriosis: Hormonal Management, Clinical Outcomes, and Opportunities for Progress.Current pharmaceutical design · 2026Review
42 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) has experienced rapid growth over the past few years, moving from the experimental to the implementation phase in various fields, including medicine. Advances in learning algorithms and theories, the availability of large datasets and improvements in computing power have contributed to breakthroughs in current AI applications. Machine learning (ML), a subset of AI, allows computers to detect patterns from large complex datasets automatically and uses these patterns to make predictions. AI is proving to be increasingly applicable to healthcare, and multiple machine learning techniques have been used to improve the performance of assisted reproductive technology (ART). Despite various challenges, the integration of AI and reproductive medicine is bound to give an essential direction to medical development in the future. In this review, we discuss the basic aspects of AI and machine learning, and we address the applications, potential limitations and challenges of AI. We also highlight the prospects and future directions in the context of reproductive medicine.
Indexed as
Identifiers
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.