Wang Jinyuan, Chen Ruxin, Long Haojun, He Junhui, Tang Masong, Su Mingxuan, Deng Renhe, Chen Yuru, Ni Rongqian, Zhao Shuhua, Rao Meng, Wang Huawei, Tang Li
Department of Reproduction and Genetics, The First Affiliated Hospital of Kunming Medical University, 295 Xichang Road, Kunming, 650032, Yunnan Province, China.
Department of Gynecological Endocrinology, Jinan Maternity and Child Care Hospital Affiliated to Shandong First Medical University, Jinan, 250001, China.
Radiol Med. 2025 Jun 23. doi: 10.1007/s11547-025-02032-9.
Integrating artificial intelligence (AI) prospected in the practical clinical management of polycystic ovary syndrome (PCOS) promised significant improvement in efficiency, interpretability, and generalizability.
To delineate a comprehensive inventory of AI-driven interventions pertinent to PCOS across diverse clinical contexts.
AI-based analytics profoundly transformed the management of PCOS, particularly in the domains of prediction, diagnosis, classification, and screening of potential complications.
Our analysis traced the principal applications of AI in PCOS management, focusing on prediction, diagnosis, classification, and screening. Furthermore, this study ventures into the potential of amalgamating and augmenting existing digital health technologies to forge an AI-augmented digital healthcare ecosystem encompassing the prevention and holistic management of PCOS. We also discuss strategic avenues that may facilitate the clinical translation of these innovative systems.
This systematic review consolidated the latest advancements in AI-driven PCOS management encompassing prediction, diagnosis, classification, and screening of potential complications, developing a digital healthcare framework tailored to the practical clinical management of PCOS.
在多囊卵巢综合征（PCOS）的实际临床管理中应用人工智能（AI）有望显著提高效率、可解释性和通用性。
描绘在不同临床环境中与PCOS相关的基于AI的干预措施的全面清单。
基于AI的分析深刻改变了PCOS的管理，特别是在预测、诊断、分类和潜在并发症筛查等领域。
我们的分析追踪了AI在PCOS管理中的主要应用，重点是预测、诊断、分类和筛查。此外，本研究探讨了融合和增强现有数字健康技术以打造涵盖PCOS预防和整体管理的AI增强型数字医疗生态系统的潜力。我们还讨论了可能促进这些创新系统临床转化的战略途径。
本系统综述巩固了AI驱动的PCOS管理的最新进展，包括潜在并发症的预测、诊断、分类和筛查，制定了适合PCOS实际临床管理的数字医疗框架。
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