ArticleCurrent urology reports2024
Artificial Intelligence for Clinical Management of Male Infertility, a Scoping Review.
Article in Current urology reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Artificial Intelligence-Driven Reproductive Bioengineering: Integrating Fertility Diagnostics, Organ-on-Chip Systems, Cryobiology and Epigenetic Safety for Precision Reproductive Medicine.Bioengineering (Basel, Switzerland) · 2026Review
- Integrating Sperm Microscopy, Environmental Exposures, and Lifestyle Factors for Male Fertility Analysis: Protocol for the Nippon Semen and Environmental Exposure Database (N-SEED) Cross-Sectional Study.JMIR research protocols · 2026Article
- An artificial intelligence real-time rare sperm detection system for intraoperative microsurgical testicular sperm extraction.Human reproduction open · 2026Article
- Environmental determinants of male infertility: emerging threats and technological interventions.Frontiers in medicine · 2026Review
- Advances in immune-inflammatory interactions within the testicular-penile microenvironment of varicocele patients: molecular mechanisms underlying erectile dysfunction and spermatogenic impairment.Frontiers in endocrinology · 2026Review
- Deep learning-based approach for sperm morphology analysis.BMC urology · 2025Review
- Genome Editing for Fertility: Unlocking the Promise of CRISPR/Cas9 in Addressing Male Infertility - A Narrative Review.Reproductive sciences (Thousand Oaks, Calif.) · 2025Review
- Prostate Cancer Treatments and Their Effects on Male Fertility: Mechanisms and Mitigation Strategies.Journal of personalized medicine · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purpose of reviewInfertility impacts one in six couples worldwide, with male infertility contributing to approximately half of these cases. However, the causes of infertility remain incompletely understood, and current methods of clinical management are cost-restrictive, time-intensive, and have limited success. Artificial intelligence (AI) may help address some of these challenges. In this review, we synthesize recent literature in AI with implications for the clinical management of male infertility. RECENT
findingsArtificial intelligence may offer opportunities for proactive, cost-effective, and efficient management of male infertility, specifically in the areas of hypogonadism, semen analysis, and interventions such as assisted reproductive technology. Patients may benefit from the integration of AI into a male infertility specialist's clinical workflow. The ability of AI to integrate large volumes of data into predictive models could help clinicians guide conversations with patients on the value of various treatment options in infertility, but caution must be taken to ensure the quality of care being delivered remains high.
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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.