EC Gynaecology

This manuscript explores the transformative intersection of Artificial Intelligence (AI) and Urogynecology, focusing on how AI technologies can address the complex challenges of pelvic floor disorders (PFDs) such as urinary incontinence and pelvic organ prolapse. These conditions affect millions globally and are often difficult to diagnose and manage due to anatomical complexity, subtle clinical findings, and variable treatment responses.

The paper outlines how AI-particularly Machine Learning (ML), Natural Language Processing (NLP), and computer vision-can enhance every stage of urogynecologic care. Applications include:

• Improved diagnostics through automated imaging analysis and urodynamic interpretation.
• Predictive modeling using Electronic Health Records (EHRs) and patient-reported outcomes.
• Personalized treatment planning for conservative and surgical interventions.
• Surgical innovation via AI-enhanced robotics and intraoperative decision support.
• Patient engagement through AI-powered chatbots and symptom monitoring tools.
• Accelerated research through automated data synthesis and risk factor discovery.

Despite its promise, AI adoption faces challenges including data quality, algorithmic bias, privacy concerns, and the need for transparency and validation. Ethical considerations such as accountability and the risk of clinical deskilling are also addressed.

The manuscript concludes that AI will not replace clinical expertise but will augment the capabilities of urogynecologists, enabling more precise, personalized, and effective care for women worldwide.

 Keywords: Artificial Intelligence (AI); Urogynecology; Pelvic Floor Disorders (PFDs); Machine Learning (ML); Natural Language Processing (NLP); Electronic Health Records (EHRs); Urinary Incontinence (UI); Fecal Incontinence (FI); Pelvic Organ Prolapse (POP)

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