OpenAlex · Aktualisierung stündlich · Letzte Aktualisierung: 14.03.2026, 01:43

Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.

Global Trends in the Use of Artificial Intelligence (AI) in Reproductive Medicine: Insights from Surveys of International Fertility Specialists

2025·1 Zitationen·Journal of IVF-WorldwideOpen Access
Volltext beim Verlag öffnen

1

Zitationen

4

Autoren

2025

Jahr

Abstract

AI is increasingly integrated into reproductive medicine, particularly in in vitro fertilization (IVF) and embryology. This study presents a comparative analysis of two global surveys conducted among IVF specialists and embryologists in 2022 (n=383) and 2025 (n=171) to assess the adoption, application, and perceptions of AI-based tools. In 2022, 24.8% of respondents used AI, primarily for embryo selection (86.3% of AI users), with strong interest in AI for sperm selection (87.5%) and embryo annotation (92.4%). By 2025, AI usage increased to 53.22% (regular or occasional use, n=91), with 21.64% (n=37) reporting regular use and 31.58% (n=54) reporting occasional use, with embryo selection remaining the dominant application (32.75%). Familiarity with AI increased notably, with 60.82% reporting at least moderate familiarity in 2025, compared to indirect evidence of lower familiarity in 2022. Key barriers to adoption included cost (38.01%) and lack of training (33.92%) in 2025, while ethical concerns and over-reliance on technology were significant risks (59.06% cited over-reliance). Both surveys highlighted optimism for AI’s potential, with 91.6% (n=351) in 2022 and 38.6% (n=66) in 2025 identifying embryo selection as a key benefit of AI. Additionally, 83.62% (n=143) of 2025 respondents were likely to invest in AI within 1–5 years, indicating strong interest in future adoption. These findings suggest a gradual increase in AI adoption, tempered by practical and ethical challenges, with implications for training, cost management, and ethical frameworks in reproductive medicine.

Ähnliche Arbeiten

Autoren

Institutionen

Themen

Artificial Intelligence in Healthcare and EducationInsurance, Mortality, Demography, Risk ManagementAssisted Reproductive Technology and Twin Pregnancy
Volltext beim Verlag öffnen