ARTIFICIAL INTELLIGENCE IN GASTROINTESTINAL SURGERY

Artificial_Intelligence_in_Gastrointestinalkapak

ARTIFICIAL INTELLIGENCE (AI) INANORECTAL AND PELVIC DISEASES

Mehmet Ömer Özduman

Kartal Koşuyolu Yüksek İhtisas Hospital, Department of Gastroenterology Surgery, İstanbul, Türkiye

Özduman MÖ. Artificial Intelligence (AI) in Anorectal and Pelvic Diseases. Çaycı HM, ed. Artificial Intelligence (AI) in Gastrointestinal Surgery. 1st ed. Ankara: Türkiye Klinikleri; 2025. p.71-78.

ABSTRACT

Diseases related to the pelvic floor and anorectal region are frequently seen in society. However, due to variations in the anatomy of this region and the complex structure of the pelvic floor muscles and their relationship with other organs, there may be delays in diagnosis and treatment. One of the biggest innovations brought by artificial intelligence in the field of medicine is segmentation and classification, where imaging techniques are used more effectively than conventional methods. Thanks to these new algorithms, the relationship between the pelvic floor muscles and pelvic organs can be shown more clearly and with fewer errors in real time in 3D. It has been shown that a more effective evaluation can be made after the optimization of anorectal manometer used in the distinction between obstructive defecation syndrome and fecal incontinence with artificial intelligence. The effectiveness of 3D reconstruction images using artificial intelligence has been demonstrated in patients with perianal fistula in showing the fistula tract, detecting the internal opening mouth of the fistula, and confirming whether the abscess drainage was sufficient. Studies have also shown that early diagnosis of precancerous lesions in the anal canal can be made using images obtained with high-resolution anoscopes and high-resolution microendoscopes with artificial intelligence. In this context, although there are studies on artificial intelligence in the differential diagnosis and treatment of anorectal and pelvic floor diseases, it is clear that studies with larger patient numbers are needed.

Keywords: Pelvic floor; Artificial intelligence; Anorectal

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