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Urogynecology telemedicine may take advantage of wearable technologies, such as urinary incontinence monitoring (which may be more accurate than bladder diaries) and post-empty residual bladder volume scanners.
Artificial Intelligence (AI) progression has become a global focus in many fields. AI consists of complex algorithms for computers to reason and performs cognitive functions, including problem-solving, outcome prediction, and decision-making. Some groundbreaking developments in obstetrics and gynecology have been published with varying successes, including automated fetal intrapartum monitoring, in vitro fertilization success prediction methods, and embryo selection models. In particular, urogynecology would benefit significantly from future advances in AI.
Developments in AI make advancements in telemedicine possible. Urogynecology telemedicine may take advantage of wearable technologies, such as urinary incontinence monitoring (which may be more accurate than bladder diaries) and post-empty residual bladder volume scanners. Wearable bladder volume control systems have recently been introduced for use in pediatric populations with nocturnal enuresis and other forms of urinary incontinence. Treatment teams may have remote access to collected data for patient care or, ultimately, could have access to the AI system.
Another practical AI application in urogynecology would involve complex management algorithms to help patients and clinicians navigate the available choices and predict the answer to care for women with different pelvic floor disorders. The advisory position of urogynecologists, gynecologists, and female urologists is complicated because multiple pathological complications of the pelvic floor often coexist, and a variety of patient factors may affect outcomes. Despite these limitations, the findings of randomized controlled trials (RCTs) are widely used as the only available estimate of outcomes for patients during therapy. Female pelvic reconstructive surgery management algorithms have lately been developed.
Intrinsic and extrinsic problems affect the development and usability of AI in urogynecology and medicine as a whole. These include new knowledge required to be acquired, new types of errors that can transpire (including an algorithm that does not predict the outcome correctly), confidentiality and ethical concerns, intellectual property issues, and the costly funding required to develop the technologies. Thus, the development of guidelines for algorithms' regulatory consent before mainstream adoption can protect both patients and physicians.