ArticleJournal of assisted reproduction and genetics2025
The perception of artificial intelligence and infertility care among patients undergoing fertility treatment.
Article in Journal of assisted reproduction and genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07308561 (The Relationship Between Quality of Life, Anxiety Levels, and Attitudes Toward Artificial Intelligence Among Women Undergoing Infertility Treatment), which is not on this map. Cited by 7 papers, 1 of them a synthesis 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.
The Relationship Between Quality of Life, Anxiety Levels, and Attitudes Toward Artificial Intelligence Among Women Undergoing Infertility Treatment
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The potential of large language models in the field of infertility: a systematic review.Journal of assisted reproduction and genetics · 2025Pooled it
- Artificial Intelligence in Embryo Selection: Current Approaches and Clinical Implications.Bioengineering (Basel, Switzerland) · 2026Review
- Fertility care in the age of algorithms: opportunities and risks of AI and social media integration in reproductive medicine.Journal of assisted reproduction and genetics · 2026Review
- The potential, perils and pitfalls of Artificial intelligence (AI) in Assisted Reproductive Technologies (ART).Reproductive biology and endocrinology : RB&E · 2026Review
- AI in Childbirth and Emerging Alternatives to Traditional Fertility Treatments.Reproductive sciences (Thousand Oaks, Calif.) · 2026Review
- Implementation readiness of artificial intelligence inFrontiers in endocrinology · 2026Review
- MAIA platform for routine clinical testing: an artificial intelligence embryo selection tool developed to assist embryologists.Scientific reports · 2025Article
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
Abstract
purposeTo characterize the opinions of patients undergoing infertility treatment on the use of artificial intelligence (AI) in their care.
methodsPatients planning or undergoing in vitro fertilization (IVF) or frozen embryo transfers were invited to complete an anonymous electronic survey from April to June 2024. The survey collected demographics, technological affinity, general perception of AI, and its applications to fertility care. Patient-reported trust of AI compared to a physician for fertility care (e.g. gamete selection, gonadotropin doing, and stimulation length) were analyzed. Descriptive statistics were calculated, and subgroup analyses by age, occupation, and parity were performed. Chi-squared tests were used to compare categorical variables.
resultsA total of 200 patients completed the survey and were primarily female (n = 193/200) and of reproductive age (mean 37 years). Patients were well educated with high technological affinity. Respondents were familiar with AI (93%) and generally supported its use in medicine (55%), but fewer trusted AI-informed reproductive care (46%). More patients disagreed (37%) that AI should be used to determine gonadotropin dose or stimulation length compared to embryo selection (26.5%; p = 0.01). In the setting of disagreement between physician and AI recommendation, patients preferred the physician-based recommendation in all treatment-related decisions. However, a larger proportion favored AI recommendations for gamete (22%) and embryo (14.5%) selection, compared to gonadotropin dosing (6.5%) or stimulation length (7.0%). Most would not be willing to pay more for AI-informed fertility care.
conclusionsIn this highly educated infertile population familiar with AI, patients still prefer physician-based recommendations compared with AI.
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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.