ArticleJournal of assisted reproduction and genetics2020
AI in the treatment of fertility: key considerations.
Article 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 26 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
26 citing papers in PubMed.
- Current state of artificial intelligence applications in assisted reproductive technology: A narrative review.Clinical and experimental reproductive medicine · 2026Article
- Automation, Artificial Intelligence (AI), and Digital Management in IVF Laboratories: Current Status, Challenges and Potential.Reproductive sciences (Thousand Oaks, Calif.) · 2026Review
- PGT-A reveals triploid embryos among normally fertilized oocytes: frequency and blastocyst features.Journal of assisted reproduction and genetics · 2026Article
- Artificial Intelligence in Routine IVF Practice.Biology · 2025Review
- The Integration of Artificial Intelligence inJournal of pharmacy & bioallied sciences · 2025Review
- The Role of Artificial Intelligence in Female Infertility Diagnosis: An Update.Journal of clinical medicine · 2025Review
- Machine learning in predicting infertility treatment success: A systematic literature review of techniques.Journal of education and health promotion · 2025Review
- Enhancing Male Fertility Through AI-Based Management of Varicoceles.Current urology reports · 2024Review
- Factors affecting biochemical pregnancy loss (BPL) in preimplantation genetic testing for aneuploidy (PGT-A) cycles: machine learning-assisted identification.Reproductive biology and endocrinology : RB&E · 2024Observational
- Harnessing Artificial Intelligence to Predict Ovarian Stimulation Outcomes in In Vitro Fertilization: Scoping Review.Journal of medical Internet research · 2024Article
- Ex ovo omnia-why don't we know more about egg quality via imaging?Biology of reproduction · 2024Review
- Fertility Preservation in the Era of Immuno-Oncology: Lights and Shadows.Journal of personalized medicine · 2024Review
- Criteria for implementing artificial intelligence systems in reproductive medicine.Clinical and experimental reproductive medicine · 2024Article
- Comparative study of machine learning approaches integrated with genetic algorithm for IVF success prediction.PloS one · 2024Article
- Artificial Intelligence in Andrology: From Semen Analysis to Image Diagnostics.The world journal of men's health · 2024Review
- Automation in ART: Paving the Way for the Future of Infertility Treatment.Reproductive sciences (Thousand Oaks, Calif.) · 2023Review
- Towards Automation in IVF: Pre-Clinical Validation of a Deep Learning-Based Embryo Grading System during PGT-A Cycles.Journal of clinical medicine · 2023Article
- New frontiers in embryo selection.Journal of assisted reproduction and genetics · 2023Review
- Data-Driven Medicine in the Diagnosis and Treatment of Infertility.Journal of clinical medicine · 2022Article
- "AI for all" is a matter of social justice.AI and ethics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) has been proposed as a potential tool to help address many of the existing problems related with empirical or subjective assessments of clinical and embryological decision points during the treatment of infertility. AI technologies are reviewed and potential areas of implementation of algorithms are discussed, highlighting the importance of following a proper path for the development and validation of algorithms, including regulatory requirements, and the need for ecosystems containing enough quality data to generate it. As evidenced by the consensus of a group of experts in fertility if properly developed, it is believed that AI algorithms may help practitioners from around the globe to standardize, automate, and improve IVF outcomes for the benefit of patients. Collaboration is required between AI developers and healthcare professionals to make this happen.
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.